DETERMINING THE WOVEN FABRIC DEFECTS BY IMPLEMENTING IMAGE COMPARISON METHODS
|
|
- Kerry Shields
- 7 years ago
- Views:
Transcription
1 (REFEREED RESEARCH) DETERMINING THE WOVEN FABRIC DEFECTS BY IMPLEMENTING IMAGE COMPARISON METHODS GÖRÜNTÜ KARŞILAŞTIRMA METODU İLE DOKUMA KUMAŞ HATALARININ TESPİTİ Cihat Okan ARIKAN 1, Hüseyin KADOĞLU 2 * 1 Ege University, Emel Akın Vocational School, İzmir, Turkey 2 Ege University, Department of Textile Engineering, İzmir, Turkey Received: Accepted: ABSTRACT Various fabric defects may occur over the surface structure during the production or use of the woven fabrics. Detection of the defects over the surface of the fabric is one of the most important factors for assessing the quality of the fabric. Fault detection is generally made by the human eye and the inspection of the fabric is a very laborious operation. In order to simplify this operation, the computer-assisted image processing methods may be used. In such methods, fabric image is electronically captured by appropriate camera systems which provides a faster comparison and also eliminates the human perceptive biases. In this study, solid-colored woven fabrics were subjected to the several image processing methods in order to detect certain fabric defects. Key Words: Woven fabrics, Image processing, Error detection, Fabric defects. ÖZET Dokuma kumaşlarda, kumaş yüzeyinde meydana gelen hatalar, kumaşın gerek üretimi sırasındaki yapısal hatalardan, gerekse kullanımı sırasında oluşan hatalardan oluşur. Kumaş yüzeyindeki hataların tespit edilmesi de kumaşın kalitesini belirlerken dikkat edilmesi gereken önemli bir faktördür. Kumaş hatalarının tespiti genellikle göz ile incelenmesi yoluyla yapıldığından oldukça zahmetli bir işlemdir. Bu işlemi basitleştirmek amacıyla, bilgisayar destekli görüntü işleme metodları yoğun olarak kullanılmaya çalışılmaktadır. Kumaş görüntüsünün elektronik kameralar ile sürekli kontrol edilerek, hem daha hızlı hem de insana bağımlı olmaktan kurtarması nedeniyle kumaş hatalarının tespitinde oldukça uygun bir yöntemdir. Bu çalışmada düz renkli dokuma kumaşlarda, görüntü işleme metodunun hata tespiti için kullanımına yönelik araştırmalar yapılmıştır. Anahtar Kelimeler: Dokuma kumaş, Görüntü işleme, Hata tespiti, Kumaş hataları. Corresponding Author: Cihat Okan Arıkan, cihat.arikan@ege.edu.tr, Tel: , INTRODUCTION Textile machines currently reached quite higher operation speeds and efficiency levels. Especially yarn spinning machinery is capable of producing high volumes at shorter time frames in line with the developments in the automation systems. The increased production capacity induced several problems for the mills which accommodate quality control departments that utilizing human eye for defect inspectione.g. failure to detect the fabric defects or necessity for employing increased number of workers in order to inspect all of the fabrics. Because of this, being capable of measuring the quality during the production has great importance for any producer as this will allow to reduce the quality control costs and increase the production efficiency. During the recent years in line with the developments at the computer technology, both software and especially optic-electronic hardware, numerical image analysis evolved as a contemporary research field (1). Chan ve Pang (2), studied the woven fabric defects over warp direction by comparing the spectral images of both defected and non-defected fabric samples. In this study it was observed that the Fourier analyses may have been employed for detecting fabric defects. The outcomes of the study revealed that it was possible to detect the combined spectral image of the normalized dimension belonged to a broken yarn both in weft direction and warp direction via utilizing upshifting at spectrum. This upshifting occurs because of the increased amount of light penetrating through the fabric which comes about by the left over emptiness by the broken yarn. It is TEKSTİL ve KONFEKSİYON 23(4),
2 possible to detect any existing double yarn via utilizing downshifting from the original image over to the defect accommodating image at the spectrum. Thus it is possible to detect punctures or holes, and similar two dimensional defects over the fabric both at warp and weft directions. Atmaca (3), carried out studies aiming to detect and classify the fundamental fabric defects encountered over knitted fabrics by utilizing Fourier analysis, histogram equalization and median filtering image processing methods. The details of fabric images were enhanced via histogram equalization. Median filtering were utilized to remove any possible noise from the images. The dimensional power spectrums were derived in accordance with the periodic structure of the fabric via Fourier analysis and the grain direction of the fabric was determined by utilizing these data. By inspecting these spectrums, it was determined the qualitative aspects for assigning the defects in related groups. Artificial neural network methods were also utilized together with image processing methods for being able to classify the results. The algorithms which were developed by this study were not applied for various diverse fabric parameters such yarn count, yarn density and fabric pattern. Arı (4), inspected the creases over various textile fabric surfaces via implementing image analysis methods. In this study the crease ratings and the crease resistance values were measured by applying frequency analysis in computer environment. 12 pieces of fabric samples having different raw materials and patterns were induced to creasing process in accordance with TS EN 390 standard and then their crease angles were measured. The images of the samples were captured via camera and transferred to computer environment. These images were converted to pixels and each of these pixels was assigned a numerical value in accordance with its gray scale enumeration within the range of in order to set up a matrix. Then, the aforementioned matrix was assessed via frequency technique analysis methods and the outcomes were interpreted regarding the raw material and pattern structure of each fabric sample. The statistical analysis revealed that obtained results were significantly reliable for different patterns providing that the raw material was kept identical and also reliable for different raw materials providing that the pattern was kept identical. Yılmaz (5) pointed out the viability of image analysis methods for designing security systems and motion analysis applications. In this study, the motion analyses were examined by background differentiation methods along with statistical tools. In this study it was observed that the outdoor images were severely influenced by light intensity variations which interfered as a substantial impeding factor. For indoor images it was possible to control the ambient light intensity via fixed light sources whereas such a compensation for outdoor environment was impossible which eventually deteriorated the outdoor trials. Besides, it evolved as a necessary to clean out the noise which occurred over the differentiation images during the processing. This necessity rendered the applied algorithm longer requiring extended processing times. Torun (6), studied on a real time defect interception system which can be utilized on circular knitting machines for textile industry. In this study, by way of processing the real time images in computer environment which were captured through a knitting machine mounted camera, it was achieved to detect some types of knitted fabric defects. The system managed to perceive defects over the knitted fabric on a Fouquet brand double plates, circular knitting machine just after 10 cm onwards the occurrence of the defect. For being able to perceive the image of exposure zone clearly, a ring shaped light source with bright LED lamps was designed to illuminate the experiment zone. After analyzing the captured images, it was observed that various defects such as holes, horizontal and vertical oil stains, needle breaks, colored yarns, thick yarns, thin yarns, fabric drops were sensed successfully. At this study, it was also achieved to set threshold boundaries for the above mentioned defects in order to stop the knitting machine if a preset range was transgressed. Jeong (7), investigated how the image processing methods to be utilized for ascertaining the warp yarn direction and the weft yarn direction. Several fabric images were acquired via a scanner and these images were subjected to various filters which revealed the validity of such a method for recognizing warp yarns and weft yarns. In this study, density estimation method (similar to Fourier analysis) was implemented. Within the context of the study, several trials were carried out for identifying the warp-weft directions over the skewed fabrics with the angle of 45 degree. The images were subjected to threshold phase filtering and then 2-D spatial gradients of the images were obtained via Sobel operator method. Hough transform was applied for deciding which lines and columns to be used. Ala (8), utilized image processing methods for digitalization of woven fabric defects in computer environment. In this study, the viability of recognizing the fabric defects by digitalization of them through several image processing methods and subsequently subjecting them to various fitters was explored. This approached was enabled several defects, especially the warp yarn related ones to be detected. Within the context of the study it was also aimed to achieve various textile related evaluations such as fabric drapeability and yarn diameter calculations via image processing utilization. Image comparison, as the designation resonates, is utilized by comparing two images and revealing the the differences between them. It is possible to compare two still images or to compare a still image with any captured one simultaneously which are being obtained via a computer connected camera. This method is developed with the aim of detecting the defects over the surface of fabric via comparing a base still fabric image with a moving fabric. The same method is also capable of detecting and even differentiating to some degree certain defects such as thick places and neps over textile yarns. Most of the defects which occur over the woven fabrics include the holes and nodes because of broken warp and filling yarns, and stains because of oil or paint drops. The weaving 326 TEKSTİL ve KONFEKSİYON 23(4), 2013
3 machine related defects evolve as structural deformations (pattern failure, pucking, hole etc.) over the fabric surface. While passing through the quality control table, the dimension and the velocity of the fabric render the visual inspection more difficult which eventually increases the probability of missing the existing defects. It is required more accurate and efficient methods for detecting the fabric defects as it is quite possible for human eye to fail to perceive a considerable amount of fabric defects via visual inspection. Consequently, the necessity and importance of automated defect detection in textile industry tend to increase at a steep pace. Automated fabric inspection yields higher accuracy standards than visual inspection hence enabling the producer to save money and time. However most of the automated systems are only capable of inspecting the manufactured fabrics in the off line mode (ex-machine status). Actually the most effective inspection method is the one which monitors the yarns or fabrics simultaneously while just being produced (10). 2. MATERIAL AND METHOD 2.1. Material In this study, it is utilized a TV card with a BT878 chip having 640x480 resolution capacity for image capturing in conjunction with a Sony CCD- TVR208E camera having 800x600 maximum resolution which is capable of automatic/manuel shutter time setting for acquiring the images. The fabric samples which are subjected to the comparison trials were obtained from Ege University Textile Engineering Department and Ege University Textile and Apparel Research & Application Center. These are selected from the single colored fabrics which have been classified previously as second quality because they were accommodating various fabric defects Method For being able to achieve the image comparison operations in computer environment, an appropriate software was developed exclusively by using Borland Delphi Developer Studio (BDS) 2006 programming language. The aforementioned software was actually capable to implement various image analysis methods such as compare two images pixel by pixel; saving the colors of all pixels and compare different image for these values; calculating the average color map value and comparing all the captured images with this reference value. However, for this study it is especially improved to focus on background differentiation method for detecting the fabric defects which is the part of comparing image areas pixel by pixel on the surface. Since the calculating these values requires very high mathematical GPU processes while the fabric flows front of the camera, the process requires very special image capturing cards (take 200 frames per second) and hardware for the expected results. In this study, capturing card is a standart VGA camera for low resolution images, so the fabric complexity is set very low to get the simple test results. The background zones are the ones which basically remain unmodified and keep the same form over the acquired images. During the motion analyses, it is achieved to determine the differentiating zones and by this way the detection of the defects via isolating the continuously identical zones. It requires to have a basic (which is rated as flawless) image beforehand for being able to differentiate the background during the image analyses. Only after acquiring such a basic image it is possible to remove the identical zones from the compared images which consequently allow ascertaining any differentiating zones. In Figure 1, the image of (a) which is rated as being a flawless fabric surface and compared to the image of (b) which is rated as being a defective woven surface (12). In the image of (c), only the differentiating zone is detected between two images. However, for the cases which were not possible to see clearly the black zone, the image of (d) was acquired via transforming the differentiation image to negative state. Figure 1. Detection of the differentiating zone via background isolation method TEKSTİL ve KONFEKSİYON 23(4),
4 It is required to establish the basic reference image (The original image page) and also the images which would be subjected to comparison (The comparison image page). The original image must be an image which was captured from the flawless zone of the fabric surface. The comparison image can be either a still image which was captured form any other zone of the fabric or an instant image which is captured directly by the camera simultaneously. When two images to be compared are selected, the differentiating zones between two images will be displayed on the Image differentiation page. At Figure 2 it is displayed the fabric image accommodating a loose warp defect as an example and at Figure 3 it is displayed the differentiating image obtained via comparison. At the image page, the identical pixels over both of the images are converted in to the black color and the differentiation image displays only the differentiated zones. Consequently, it is achieved to reveal the defective zones which induce differentiation over the surface of fabric. Figure 2. Image comparison screen Figure 3. The differentiating image obtained via comparison Figure 4. The settings which are used for image comparison analysis 328 TEKSTİL ve KONFEKSİYON 23(4), 2013
5 The differentiation image which is acquired via comparison analysis is an 8-bit gray scale image. Color shade related fabric defects usually show themselves as pale colored zones over the differentiation image. In case of insufficient visible details, please select Negatifini göster (Display as negative) option from as shown at Figure 4 for being able to review the negative image to explore an another approach. In the negative image state, the details within the dark zones will reveal themselves clearer. If the image dimensions happen to be extremely large, please select the Ekrana sığdır (Fit to screen) option for being able to review the image at full width on the parent window dimensions. The equivalency ratios for the compared images are displayed at the bottom of the screen as percentiles (%). For instance, "0.58% difference" statement means there is a 0.58% equivalency difference between two images. This value has been calculated by automatically by using pixel comparison method according to the reference image area and it shows that in 1000 pixels on the captured surface, 58 pixels are identifically not equal for compared images (reference image and the captured image). The calculated value is very small (little than 1) so the difference between two fabric is not important at this point. This difference usually varies in accordance with the dimension and coverage of the defect. For defects such as holes or ruptures this ratio may reach up to 10-15% level, for warp or weft yarn related defects this ratio dwells around 1-8% level. These values vary by the fabric type, light density on the area, colors on the fabrics etc.. So, it must be determine the best value by capturing images about 5-10 meters and check the value for fabric surface (mostly without any defect). The level should be accept as non-defect value and process will continue with that value. In this study, according to the fabric surface, the values are determined as 0-2% has no errors, 2-4% faint errors, 5-8% evident fabric defects and 8% and above are very big surface defects. It is possible to specify any value exceeding the predetermined range as a defect. It is also possible to save any detected differentiating image in a specified folder for reviewing later by selecting Hata oluştuğunda görüntüyü klasöre kaydet (Save the image to folder) when a defect is occurred option from the right side of the settings tab. 3. RESULTS AND DISCUSSIONS The implemented image processing methods within the context of this study enables to detect various fabric defects. The experimental setting is based on basic patterned and solid colored defective fabric samples. The operational state of the system requires appropriate software but also the spinning and weaving machines require to be structurally modified for achieving an integrable outfit. During the analyses of yarn and fabric defects, the resolution level and image capturing speed of the camera fell behind the required range and the vibrations which are induced by the dynamic forces of the weaving machine rendered the superstructure of the camera carrier unoperational for capturing full width fabric images. Because of these factors, this study was carried on by using several images which were captured over the fabric samples. Numerous comparisons were employed between basic flawless fabric images and defective fabric images and when a certain degree of differentiation was detected exceeding the preset values, such a detection was specified as an indication of a fabric defect. The technical limitations of the available camera and image capturing devices restrained the scope of the study significantly. Nevertheless it is observed that it is possible to capture some sort of fabric defects to a certain degree even with a simple optic system. Thus it is quite possible to suggest that especially sophisticated optic-electronic systems have great potential for the automation of fabric defect detection operations. Therefore this study conveys experimental data for the viability of such systems. It is quite possible to manufacture compact and versatile computer aided opticelectronic defect detection devices by implementing advanced image analysis methods and algorithms. The results of this study may propose a functional interim stage for future researches. REFERENCES 1. Akyol, B. Ö., 1999, Sayısal Görüntü İşlemede Görüntü Karşılaştırma, Gazi Üniversitesi, Y.L. Tezi. 2. Chan, C. and Pang, G., 2000, Fabric defect detection by Fourier analysis, IEEE Transactions on Industry Applications, 36(5): Atmaca, V., 2005, Örme Kumaşlardaki Üretim Hatalarının Görüntü İşleme Teknikleri ile Otomatik Tespiti ve Sınıflandırılması, İstanbul Teknik Üniversitesi, Y.L. Tezi. 4. Arı, İ., 2006, Dokuma Kumaşlarda Oluşan Kırışıklıkların Görüntü Analizi Yöntemi İle Değerlendirilmesi, İstanbul Üniversitesi, Y.L. Tezi. 5. Yılmaz, A., 2007, Kamera Kullanılarak Görüntü İşleme Yoluyla Gerçek Zamanlı Güvenlik Uygulaması, Haliç Üniversitesi, Y.L. Tezi. 6. Torun, T. K., 2007, Yuvarlak Örme Makineleri İçin On-Line Hata Kontrol Sistemi Tasarlanması, Ege Üniversitesi Tekstil Mühendisliği, Y.L. Tezi. 7. Jeong, Y., 2008, Novel Technique to Align Fabric in Image Analysis, Textile Research Journal, Issue: 78, p: Ala, D. Ö., Ağustos 2008, Sayısal Görüntü İşlemede Görüntü Karşılaştırma, Gazi Üniversitesi, Y.L. Tezi. 9. Kumar, A., Pang, G., 2002, Defect detection in textured materials using Gabor filters, IEEE Transactions on Industry Applications, 38(2): , April Sari-Sarraf, H., Goddard, J. Chan, C. and Pang, G., 1999, Fabric defect detection by Fourier analysis, IEEE Transactions on Industry Applications, 36(6): Chan, C. and Pang, G., 2002, Fabric defect detection by Fourier analysis, IEEE Transactions on Industry Applications, 38(2): Tan, O., Taşkın, C., 2006, Kumaş Hataları. TEKSTİL ve KONFEKSİYON 23(4),
Camera Technology Guide. Factors to consider when selecting your video surveillance cameras
Camera Technology Guide Factors to consider when selecting your video surveillance cameras Introduction Investing in a video surveillance system is a smart move. You have many assets to protect so you
More informationWHITE PAPER. Methods for Measuring Flat Panel Display Defects and Mura as Correlated to Human Visual Perception
Methods for Measuring Flat Panel Display Defects and Mura as Correlated to Human Visual Perception Methods for Measuring Flat Panel Display Defects and Mura as Correlated to Human Visual Perception Abstract
More informationElectronic Systems Engineering Department, Turkish Naval Academy, Naval Sciences and Engineering Institute, Tuzla, Istanbul 1 moun@dho.edu.
Journal of Naval Science and Engineering 2013, Vol.9, No.2, pp.66-71 LABVIEW BASED TARGET RECOGNITION AND TRACKING SYSTEM M.Oğuzhan ÜN, 1 Lt.Jr.Gr. Asst.Prof. Mustafa YAĞIMLI 2, Naval Captain Associate
More informationUltrasonic Wave Propagation Review
Ultrasonic Wave Propagation Review Presented by: Sami El-Ali 1 1. Introduction Ultrasonic refers to any study or application of sound waves that are higher frequency than the human audible range. Ultrasonic
More informationAnalecta Vol. 8, No. 2 ISSN 2064-7964
EXPERIMENTAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS IN ENGINEERING PROCESSING SYSTEM S. Dadvandipour Institute of Information Engineering, University of Miskolc, Egyetemváros, 3515, Miskolc, Hungary,
More informationDefect detection of gold-plated surfaces on PCBs using Entropy measures
Defect detection of gold-plated surfaces on PCBs using ntropy measures D. M. Tsai and B. T. Lin Machine Vision Lab. Department of Industrial ngineering and Management Yuan-Ze University, Chung-Li, Taiwan,
More informationEVIDENCE PHOTOGRAPHY TEST SPECIFICATIONS MODULE 1: CAMERA SYSTEMS & LIGHT THEORY (37)
EVIDENCE PHOTOGRAPHY TEST SPECIFICATIONS The exam will cover evidence photography involving crime scenes, fire scenes, accident scenes, aircraft incident scenes, surveillances and hazardous materials scenes.
More informationScanners and How to Use Them
Written by Jonathan Sachs Copyright 1996-1999 Digital Light & Color Introduction A scanner is a device that converts images to a digital file you can use with your computer. There are many different types
More informationChoosing a digital camera for your microscope John C. Russ, Materials Science and Engineering Dept., North Carolina State Univ.
Choosing a digital camera for your microscope John C. Russ, Materials Science and Engineering Dept., North Carolina State Univ., Raleigh, NC One vital step is to choose a transfer lens matched to your
More informationAutomatic Detection of PCB Defects
IJIRST International Journal for Innovative Research in Science & Technology Volume 1 Issue 6 November 2014 ISSN (online): 2349-6010 Automatic Detection of PCB Defects Ashish Singh PG Student Vimal H.
More informationAutomotive Applications of 3D Laser Scanning Introduction
Automotive Applications of 3D Laser Scanning Kyle Johnston, Ph.D., Metron Systems, Inc. 34935 SE Douglas Street, Suite 110, Snoqualmie, WA 98065 425-396-5577, www.metronsys.com 2002 Metron Systems, Inc
More informationEPSON SCANNING TIPS AND TROUBLESHOOTING GUIDE Epson Perfection 3170 Scanner
EPSON SCANNING TIPS AND TROUBLESHOOTING GUIDE Epson Perfection 3170 Scanner SELECT A SUITABLE RESOLUTION The best scanning resolution depends on the purpose of the scan. When you specify a high resolution,
More informationVECTORAL IMAGING THE NEW DIRECTION IN AUTOMATED OPTICAL INSPECTION
VECTORAL IMAGING THE NEW DIRECTION IN AUTOMATED OPTICAL INSPECTION Mark J. Norris Vision Inspection Technology, LLC Haverhill, MA mnorris@vitechnology.com ABSTRACT Traditional methods of identifying and
More informationImage Processing Based Automatic Visual Inspection System for PCBs
IOSR Journal of Engineering (IOSRJEN) ISSN: 2250-3021 Volume 2, Issue 6 (June 2012), PP 1451-1455 www.iosrjen.org Image Processing Based Automatic Visual Inspection System for PCBs Sanveer Singh 1, Manu
More informationAutomatic and Objective Measurement of Residual Stress and Cord in Glass
Automatic and Objective Measurement of Residual Stress and Cord in Glass GlassTrend - ICG TC15/21 Seminar SENSORS AND PROCESS CONTROL 13-14 October 2015, Eindhoven Henning Katte, ilis gmbh copyright ilis
More informationDEVELOPING AN ALGORITHM FOR DEFECT DETECTION OF DENIM FABRIC: GABOR FILTER METHOD
(REFEREED RESEARCH) DEVELOPING AN ALGORITHM FOR DEFECT DETECTION OF DENIM FABRIC: GABOR FILTER METHOD DENİM KUMAŞIN HATA DENETİMİ İÇİN BİR ALGORİTMA GELİŞTİRİLMESİ: GABOR FİLTRE YÖNTEMİ H. İbrahim ÇELİK
More informationWhite paper. CCD and CMOS sensor technology Technical white paper
White paper CCD and CMOS sensor technology Technical white paper Table of contents 1. Introduction to image sensors 3 2. CCD technology 4 3. CMOS technology 5 4. HDTV and megapixel sensors 6 5. Main differences
More informationModule 13 : Measurements on Fiber Optic Systems
Module 13 : Measurements on Fiber Optic Systems Lecture : Measurements on Fiber Optic Systems Objectives In this lecture you will learn the following Measurements on Fiber Optic Systems Attenuation (Loss)
More informationDetachable DIY Door Viewer Camera for Home / Office Safety. Installation Manual. (* This is a patented product, do not copy) IA Technologies Inc.
Detachable DIY Door Viewer Camera for Home / Office Safety Installation Manual (* This is a patented product, do not copy) IA Technologies Inc. www.iat101.com www.peephole-store.com Table of contents:
More informationPhotography of Cultural Heritage items
Photography of Cultural Heritage items A lot of people only get to know art pieces through photographic reproductions. Nowadays with digital imaging far more common than traditional analogue photography,
More informationEffect of Lycra Extension Percent on Single Jersey Knitted Fabric Properties
Effect of Lycra Extension Percent on Single Jersey Knitted Fabric Properties R. Sadek, A. M. El-Hossini, A. S. Eldeeb, A.A. Yassen Mansoura University, Textile Engineering Department, Mansoura, EGYPT Correspondence
More informationQUALITY TESTING OF WATER PUMP PULLEY USING IMAGE PROCESSING
QUALITY TESTING OF WATER PUMP PULLEY USING IMAGE PROCESSING MRS. A H. TIRMARE 1, MS.R.N.KULKARNI 2, MR. A R. BHOSALE 3 MR. C.S. MORE 4 MR.A.G.NIMBALKAR 5 1, 2 Assistant professor Bharati Vidyapeeth s college
More information3D Scanner using Line Laser. 1. Introduction. 2. Theory
. Introduction 3D Scanner using Line Laser Di Lu Electrical, Computer, and Systems Engineering Rensselaer Polytechnic Institute The goal of 3D reconstruction is to recover the 3D properties of a geometric
More informationDigitization of Old Maps Using Deskan Express 5.0
Dražen Tutić *, Miljenko Lapaine ** Digitization of Old Maps Using Deskan Express 5.0 Keywords: digitization; scanner; scanning; old maps; Deskan Express 5.0. Summary The Faculty of Geodesy, University
More informationGEOENGINE MSc in Geomatics Engineering (Master Thesis) Anamelechi, Falasy Ebere
Master s Thesis: ANAMELECHI, FALASY EBERE Analysis of a Raster DEM Creation for a Farm Management Information System based on GNSS and Total Station Coordinates Duration of the Thesis: 6 Months Completion
More informationWEAVING TECHNOLOGY II
WEAVING TECHNOLOGY II Secondary Motions of Weaving Prof.Dr. Emel Önder Ass.Prof.Dr.Ömer Berk Berkalp Other Loom Mechanisms A series of other mechanisms is used in the interest of productivity and quality.
More informationWhite paper. In the best of light The challenges of minimum illumination
White paper In the best of light The challenges of minimum illumination Table of contents 1. Introduction 3 2. The puzzle of light sensitivity 3 3. Do not be fooled! 5 4. Making the smarter choice 6 1.
More informationColour Image Segmentation Technique for Screen Printing
60 R.U. Hewage and D.U.J. Sonnadara Department of Physics, University of Colombo, Sri Lanka ABSTRACT Screen-printing is an industry with a large number of applications ranging from printing mobile phone
More informationDigital Image Requirements for New Online US Visa Application
Digital Image Requirements for New Online US Visa Application As part of the electronic submission of your DS-160 application, you will be asked to provide an electronic copy of your photo. The photo must
More informationRodenstock Photo Optics
Rogonar Rogonar-S Rodagon Apo-Rodagon N Rodagon-WA Apo-Rodagon-D Accessories: Modular-Focus Lenses for Enlarging, CCD Photos and Video To reproduce analog photographs as pictures on paper requires two
More informationHigh Capacity Hot Air Dryer
High Capacity Hot Air Dryer MADE IN AUSTRIA autumn 2015 www.zimmer-austria.com page 1 Hot air dryer type: Compact HC The modular construction of the high efficiency and powerful hot air nozzle dryer is
More informationHigh Resolution Spatial Electroluminescence Imaging of Photovoltaic Modules
High Resolution Spatial Electroluminescence Imaging of Photovoltaic Modules Abstract J.L. Crozier, E.E. van Dyk, F.J. Vorster Nelson Mandela Metropolitan University Electroluminescence (EL) is a useful
More informationCHAPTER 1. Introduction to CAD/CAM/CAE Systems
CHAPTER 1 1.1 OVERVIEW Introduction to CAD/CAM/CAE Systems Today s industries cannot survive worldwide competition unless they introduce new products with better quality (quality, Q), at lower cost (cost,
More informationSheet Metal Shearing & Bending
Training Objective After watching the program and reviewing this printed material, the viewer will gain a knowledge and understanding of the principles and machine methods of shearing and bending sheetmetal
More informationLaserlyte-Flex Alignment System
Laserlyte-Flex Alignment System LaserLyte-Flex The LaserLyte-Flex Alignment System is a unique, interchangeable, low cost plug and play laser system. Designed specifically for aligning and positioning
More informationHigh-speed Photography with a Still Digital Camera
High-speed Photography with a Still Digital Camera Matthew Moore North Carolina School of Science and Math 1219 Broad St. Durham, NC 27705 Sponsored By Dr. Loren Winters 12/2/99 Abstract High-speed photography
More informationEpson 3LCD Technology A Technical Analysis and Comparison against 1-Chip DLP Technology
An Epson White Paper Epson 3LCD Technology A Technical Analysis and Comparison against 1-Chip DLP Technology Epson South Asia & Southeast Asia June 2010 About 3LCD Technology 3LCD Technology is the world
More informationThe Scientific Data Mining Process
Chapter 4 The Scientific Data Mining Process When I use a word, Humpty Dumpty said, in rather a scornful tone, it means just what I choose it to mean neither more nor less. Lewis Carroll [87, p. 214] In
More informationMobile Robot FastSLAM with Xbox Kinect
Mobile Robot FastSLAM with Xbox Kinect Design Team Taylor Apgar, Sean Suri, Xiangdong Xi Design Advisor Prof. Greg Kowalski Abstract Mapping is an interesting and difficult problem in robotics. In order
More informationDoppler. Doppler. Doppler shift. Doppler Frequency. Doppler shift. Doppler shift. Chapter 19
Doppler Doppler Chapter 19 A moving train with a trumpet player holding the same tone for a very long time travels from your left to your right. The tone changes relative the motion of you (receiver) and
More informationAssessment. Presenter: Yupu Zhang, Guoliang Jin, Tuo Wang Computer Vision 2008 Fall
Automatic Photo Quality Assessment Presenter: Yupu Zhang, Guoliang Jin, Tuo Wang Computer Vision 2008 Fall Estimating i the photorealism of images: Distinguishing i i paintings from photographs h Florin
More informationVisualization and Feature Extraction, FLOW Spring School 2016 Prof. Dr. Tino Weinkauf. Flow Visualization. Image-Based Methods (integration-based)
Visualization and Feature Extraction, FLOW Spring School 2016 Prof. Dr. Tino Weinkauf Flow Visualization Image-Based Methods (integration-based) Spot Noise (Jarke van Wijk, Siggraph 1991) Flow Visualization:
More informationScanning Acoustic Microscopy Training
Scanning Acoustic Microscopy Training This presentation and images are copyrighted by Sonix, Inc. They may not be copied, reproduced, modified, published, uploaded, posted, transmitted, or distributed
More informationE70 Rear-view Camera (RFK)
Table of Contents (RFK) Subject Page Introduction..................................................3 Rear-view Camera..............................................3 Input/Output...................................................4
More informationHistograms& Light Meters HOW THEY WORK TOGETHER
Histograms& Light Meters HOW THEY WORK TOGETHER WHAT IS A HISTOGRAM? Frequency* 0 Darker to Lighter Steps 255 Shadow Midtones Highlights Figure 1 Anatomy of a Photographic Histogram *Frequency indicates
More informationBARE PCB INSPECTION BY MEAN OF ECT TECHNIQUE WITH SPIN-VALVE GMR SENSOR
BARE PCB INSPECTION BY MEAN OF ECT TECHNIQUE WITH SPIN-VALVE GMR SENSOR K. Chomsuwan 1, S. Yamada 1, M. Iwahara 1, H. Wakiwaka 2, T. Taniguchi 3, and S. Shoji 4 1 Kanazawa University, Kanazawa, Japan;
More informationStatic Environment Recognition Using Omni-camera from a Moving Vehicle
Static Environment Recognition Using Omni-camera from a Moving Vehicle Teruko Yata, Chuck Thorpe Frank Dellaert The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 USA College of Computing
More informationColor Measurement Methods for Textile Fabrics
Color Measurement Methods for Textile Fabrics One of the key elements in successfully utilizing a color control system is the accurate and repeatable measurement of the samples being evaluated. Poor technique
More informationMotion Activated Camera User Manual
Brinno MAC200 User Manual Last Modified on 12/23/2015 7:51 pm EST Motion Activated Camera User Manual www.brinno.com Register@online http://www.brinno.com/support/register.html contact us: customerservice@brinno.com
More informationHow an electronic shutter works in a CMOS camera. First, let s review how shutters work in film cameras.
How an electronic shutter works in a CMOS camera I have been asked many times how an electronic shutter works in a CMOS camera and how it affects the camera s performance. Here s a description of the way
More informationUsing MATLAB to Measure the Diameter of an Object within an Image
Using MATLAB to Measure the Diameter of an Object within an Image Keywords: MATLAB, Diameter, Image, Measure, Image Processing Toolbox Author: Matthew Wesolowski Date: November 14 th 2014 Executive Summary
More informationFace detection is a process of localizing and extracting the face region from the
Chapter 4 FACE NORMALIZATION 4.1 INTRODUCTION Face detection is a process of localizing and extracting the face region from the background. The detected face varies in rotation, brightness, size, etc.
More informationComputer Animation of Extensive Air Showers Interacting with the Milagro Water Cherenkov Detector
Computer Animation of Extensive Air Showers Interacting with the Milagro Water Cherenkov Detector Miguel F. Morales Department of Physics, University of California, Santa Cruz, CA 95064, USA We employ
More informationDigital Energy ITI. Instrument Transformer Basic Technical Information and Application
g Digital Energy ITI Instrument Transformer Basic Technical Information and Application Table of Contents DEFINITIONS AND FUNCTIONS CONSTRUCTION FEATURES MAGNETIC CIRCUITS RATING AND RATIO CURRENT TRANSFORMER
More informationAN EXPERT SYSTEM TO ANALYZE HOMOGENEITY IN FUEL ELEMENT PLATES FOR RESEARCH REACTORS
AN EXPERT SYSTEM TO ANALYZE HOMOGENEITY IN FUEL ELEMENT PLATES FOR RESEARCH REACTORS Cativa Tolosa, S. and Marajofsky, A. Comisión Nacional de Energía Atómica Abstract In the manufacturing control of Fuel
More informationInvestigation of Color Aliasing of High Spatial Frequencies and Edges for Bayer-Pattern Sensors and Foveon X3 Direct Image Sensors
Investigation of Color Aliasing of High Spatial Frequencies and Edges for Bayer-Pattern Sensors and Foveon X3 Direct Image Sensors Rudolph J. Guttosch Foveon, Inc. Santa Clara, CA Abstract The reproduction
More informationModelling, Extraction and Description of Intrinsic Cues of High Resolution Satellite Images: Independent Component Analysis based approaches
Modelling, Extraction and Description of Intrinsic Cues of High Resolution Satellite Images: Independent Component Analysis based approaches PhD Thesis by Payam Birjandi Director: Prof. Mihai Datcu Problematic
More informationComputer Vision for Quality Control in Latin American Food Industry, A Case Study
Computer Vision for Quality Control in Latin American Food Industry, A Case Study J.M. Aguilera A1, A. Cipriano A1, M. Eraña A2, I. Lillo A1, D. Mery A1, and A. Soto A1 e-mail: [jmaguile,aciprian,dmery,asoto,]@ing.puc.cl
More informationSimple. Intelligent. The SIMATIC VS 100 Series. simatic MACHINE VISION. www.siemens.com/machine-vision
Simple. Intelligent. The SIMATIC VS 100 Series. simatic MACHINE VISION www.siemens.com/machine-vision simatic Intelligence that pays off In answer to the problem of steadily increasing clock-pulse rates
More informationHigh-Performance Signature Recognition Method using SVM
High-Performance Signature Recognition Method using SVM Saeid Fazli Research Institute of Modern Biological Techniques University of Zanjan Shima Pouyan Electrical Engineering Department University of
More informationPerformance testing for Precision 500D Classical R/F System
Performance testing for Precision 500D Classical R/F System John M. Boudry, Ph.D. Image Quality Systems Engineer GE Healthcare Technologies Outline System background Image Quality Signature Test (IQST)
More informationGenerator Stator Protection, under/over voltage, under /over frequency and unbalanced loading. Ramandeep Kaur Aujla S.NO 250447392
1 Generator Stator Protection, under/over voltage, under /over frequency and unbalanced loading By Ramandeep Kaur Aujla S.NO 250447392 ES 586b: Theory and applications of protective relays Department of
More informationApplication Note #503 Comparing 3D Optical Microscopy Techniques for Metrology Applications
Screw thread image generated by WLI Steep PSS angles WLI color imaging Application Note #503 Comparing 3D Optical Microscopy Techniques for Metrology Applications 3D optical microscopy is a mainstay metrology
More informationPrimeview Indoor LED Display
Primeview Indoor LED Display Unique by Design Large Venue Retail Broadcast Financial Primeview Indoor LED Display Unique by Design Primeview s Indoor LED Video Wall solutions are the most ideal system
More informationInternational Year of Light 2015 Tech-Talks BREGENZ: Mehmet Arik Well-Being in Office Applications Light Measurement & Quality Parameters
www.led-professional.com ISSN 1993-890X Trends & Technologies for Future Lighting Solutions ReviewJan/Feb 2015 Issue LpR 47 International Year of Light 2015 Tech-Talks BREGENZ: Mehmet Arik Well-Being in
More informationFixplot Instruction Manual. (data plotting program)
Fixplot Instruction Manual (data plotting program) MANUAL VERSION2 2004 1 1. Introduction The Fixplot program is a component program of Eyenal that allows the user to plot eye position data collected with
More informationDigital Camera Imaging Evaluation
Digital Camera Imaging Evaluation Presenter/Author J Mazzetta, Electro Optical Industries Coauthors Dennis Caudle, Electro Optical Industries Bob Wageneck, Electro Optical Industries Contact Information
More informationVisual Servoing Methodology for Selective Tree Pruning by Human-Robot Collaborative System
Ref: C0287 Visual Servoing Methodology for Selective Tree Pruning by Human-Robot Collaborative System Avital Bechar, Victor Bloch, Roee Finkelshtain, Sivan Levi, Aharon Hoffman, Haim Egozi and Ze ev Schmilovitch,
More informationCorrecting the Lateral Response Artifact in Radiochromic Film Images from Flatbed Scanners
Correcting the Lateral Response Artifact in Radiochromic Film Images from Flatbed Scanners Background The lateral response artifact (LRA) in radiochromic film images from flatbed scanners was first pointed
More informationWHITE PAPER DECEMBER 2010 CREATING QUALITY BAR CODES FOR YOUR MOBILE APPLICATION
DECEMBER 2010 CREATING QUALITY BAR CODES FOR YOUR MOBILE APPLICATION TABLE OF CONTENTS 1 Introduction...3 2 Printed bar codes vs. mobile bar codes...3 3 What can go wrong?...5 3.1 Bar code Quiet Zones...5
More informationWOOD WEAR TESTING USING TRIBOMETER
WOOD WEAR TESTING USING TRIBOMETER Prepared by Duanjie Li, PhD 6 Morgan, Ste156, Irvine CA 92618 P: 949.461.9292 F: 949.461.9232 nanovea.com Today's standard for tomorrow's materials. 2015 NANOVEA INTRO
More informationMethod of Mesh Fabric Defect Inspection Based on Machine Vision
Method of Mesh Fabric Defect Inspection Based on Machine Vision Guodong Sun, PhD, Huan Li, Xin Dai, Daxing Zhao, PhD, Wei Feng Hubei University of Technology, Wuhan, Hubei Province CHINA Correspondence
More informationLIST OF CONTENTS CHAPTER CONTENT PAGE DECLARATION DEDICATION ACKNOWLEDGEMENTS ABSTRACT ABSTRAK
vii LIST OF CONTENTS CHAPTER CONTENT PAGE DECLARATION DEDICATION ACKNOWLEDGEMENTS ABSTRACT ABSTRAK LIST OF CONTENTS LIST OF TABLES LIST OF FIGURES LIST OF NOTATIONS LIST OF ABBREVIATIONS LIST OF APPENDICES
More informationThe infrared camera NEC Thermo tracer TH7102WL (1) (IR
PERIODICUM BIOLOGORUM UDC 57:61 VOL. 108, No 4,????, 2006 CODEN PDBIAD ISSN 0031-5362 Original scientific paper ThermoWEB-Remote Control and Measurement of Temperature over the Web D. KOLARI] K. SKALA
More informationReflectance Measurements of Materials Used in the Solar Industry. Selecting the Appropriate Accessories for UV/Vis/NIR Measurements.
T e c h n i c a l N o t e Reflectance Measurements of Materials Used in the Solar Industry UV/Vis/NIR Author: Dr. Jeffrey L. Taylor PerkinElmer, Inc. 710 Bridgeport Avenue Shelton, CT 06484 USA Selecting
More informationPlanetary Imaging Workshop Larry Owens
Planetary Imaging Workshop Larry Owens Lowell Observatory, 1971-1973 Backyard Telescope, 2005 How is it possible? How is it done? Lowell Observatory Sequence,1971 Acquisition E-X-P-E-R-I-M-E-N-T-A-T-I-O-N!
More informationMACHINE VISION FOR SMARTPHONES. Essential machine vision camera requirements to fulfill the needs of our society
MACHINE VISION FOR SMARTPHONES Essential machine vision camera requirements to fulfill the needs of our society INTRODUCTION With changes in our society, there is an increased demand in stateof-the art
More informationAutomatic 3D Reconstruction via Object Detection and 3D Transformable Model Matching CS 269 Class Project Report
Automatic 3D Reconstruction via Object Detection and 3D Transformable Model Matching CS 69 Class Project Report Junhua Mao and Lunbo Xu University of California, Los Angeles mjhustc@ucla.edu and lunbo
More informationA technical overview of the Fuel3D system.
A technical overview of the Fuel3D system. Contents Introduction 3 How does Fuel3D actually work? 4 Photometric imaging for high-resolution surface detail 4 Optical localization to track movement during
More informationShutter & Aperture Research & Demonstrations
Camera Exercises ART-162 Winter 2013 version CX-162-CameraExercises-2013W.A3 Page 1 CX-2.1 Shutter & Aperture Research & Demonstrations 10 Explanations in part 2 are well done: submit written answers.
More informationAxioCam MR The All-round Camera for Biology, Medicine and Materials Analysis Digital Documentation in Microscopy
Microscopy from Carl Zeiss AxioCam MR The All-round Camera for Biology, Medicine and Materials Analysis Digital Documentation in Microscopy New Dimensions in Performance AxioCam MR from Carl Zeiss Both
More informationAbout the Render Gallery
About the Render Gallery All of your completed rendered images are available online from the Render Gallery page. Images in the gallery are grouped in collections according to the source document (RVT
More informationAn Overview of Digital Imaging Systems for Radiography and Fluoroscopy
An Overview of Digital Imaging Systems for Radiography and Fluoroscopy Michael Yester, Ph.D. University of Alabama at Birmingham Outline Introduction Imaging Considerations Receptor Properties General
More informationWAVELENGTH OF LIGHT - DIFFRACTION GRATING
PURPOSE In this experiment we will use the diffraction grating and the spectrometer to measure wavelengths in the mercury spectrum. THEORY A diffraction grating is essentially a series of parallel equidistant
More informationVideo surveillance camera Installation Guide
Video surveillance camera Installation Guide TV7085 TV7086 TV7087 TV7088 14 1. Preface Dear Customer, Thank you for purchasing this Eyseo digital surveillance camera. You made the right decision in choosing
More informationMODERN VOXEL BASED DATA AND GEOMETRY ANALYSIS SOFTWARE TOOLS FOR INDUSTRIAL CT
MODERN VOXEL BASED DATA AND GEOMETRY ANALYSIS SOFTWARE TOOLS FOR INDUSTRIAL CT C. Reinhart, C. Poliwoda, T. Guenther, W. Roemer, S. Maass, C. Gosch all Volume Graphics GmbH, Heidelberg, Germany Abstract:
More informationBCC Multi Stripe Wipe
BCC Multi Stripe Wipe The BCC Multi Stripe Wipe is a similar to a Horizontal or Vertical Blind wipe. It offers extensive controls to randomize the stripes parameters. The following example shows a Multi
More informationARAŞTIRMA MAKALESİ / RESEARCH ARTICLE
ANADOLU ÜNİVERSİTESİ BİLİM VE TEKNOLOJİ DERGİSİ A ANADOLU UNIVERSITY JOURNAL OF SCIENCE AND TECHNOLOGY A Applied Sciences and Engineering Cilt/Vol.: 13-Sayı/No: 2 : 121-126 (2012) ARAŞTIRMA MAKALESİ /
More informationAlpy guiding User Guide. Olivier Thizy (olivier.thizy@shelyak.com) François Cochard (francois.cochard@shelyak.com)
Alpy guiding User Guide Olivier Thizy (olivier.thizy@shelyak.com) François Cochard (francois.cochard@shelyak.com) DC0017A : april 2013 Alpy guiding module User Guide Olivier Thizy (olivier.thizy@shelyak.com)
More informationPhysics 441/2: Transmission Electron Microscope
Physics 441/2: Transmission Electron Microscope Introduction In this experiment we will explore the use of transmission electron microscopy (TEM) to take us into the world of ultrasmall structures. This
More informationRealization of a UV fisheye hyperspectral camera
Realization of a UV fisheye hyperspectral camera Valentina Caricato, Andrea Egidi, Marco Pisani and Massimo Zucco, INRIM Outline Purpose of the instrument Required specs Hyperspectral technique Optical
More informationInterference. Physics 102 Workshop #3. General Instructions
Interference Physics 102 Workshop #3 Name: Lab Partner(s): Instructor: Time of Workshop: General Instructions Workshop exercises are to be carried out in groups of three. One report per group is due by
More informationSEWING MAINTENANCE CHECKLIST
SEWING MAINTENANCE CHECKLIST Many Retail, Brand-name Marketing, Mail Order and Sourcing Companies are visiting existing and potential Contractor sewing facilities and evaluating their sewing capabilities
More informationWhy is lighting in the workplace important?
OSH Brief No. 3c Why is lighting in the workplace important? From the workers perspective, poor lighting at work can lead to eye strain, fatigue, headaches, stress and accidents. On the other hand, too
More informationRegistration of X ray mammograms and 3 dimensional speed of sound images of the female breast
Diploma Thesis 2008 Registration of X ray mammograms and 3 dimensional speed of sound images of the female breast by Marie Holzapfel - Student number: 164122 - - Course: TIT05ANS - Company: Forschungszentrum
More informationBasler. Line Scan Cameras
Basler Line Scan Cameras High-quality line scan technology meets a cost-effective GigE interface Real color support in a compact housing size Shading correction compensates for difficult lighting conditions
More informationBasler. Area Scan Cameras
Basler Area Scan Cameras VGA to 5 megapixels and up to 210 fps Selected high quality Sony and Kodak CCD sensors Powerful Gigabit Ethernet interface Superb image quality at all resolutions and frame rates
More informationDigital Photography Composition. Kent Messamore 9/8/2013
Digital Photography Composition Kent Messamore 9/8/2013 Photography Equipment versus Art Last week we focused on our Cameras Hopefully we have mastered the buttons and dials by now If not, it will come
More informationBasic Manual Control of a DSLR Camera
Basic Manual Control of a DSLR Camera Naixn 2008 Photographers don t just take photographs - they make them! Produced by Yon Ankersmit for curious-eye.com 2009 Digital Single Lens Reflex Camera The basic
More informationCOMPARISON BETWEEN MECHANICAL PROPERTIES OF FABRICS WOVEN FROM COMPACT AND RING SPUN YARNS
COMPARISON BETWEEN MECHANICAL PROPERTIES OF FABRICS WOVEN FROM COMPACT AND RING SPUN YARNS Alsaid. A. Almetwally 1 and Mona. M. Salem 2 Textile Division, National Research Centre, Egypt 1 e-mail: saaa_2510@yahoo.com
More information