One picture is worth more than ten thousand words. Anonymous Introduction to Digital ImageProcessing(PECS5406) Kalyan Kumar Barik Synergy 1
Books R.C. Gonzalez, R.E. Woods, Digital Image Processing, 3rd Edition, Pearson Education S.Sridhar, Digital Image Processing, Oxford University Press, 2011 Anil K Jain, Fundamentals of Digital Image Processing R C Gonzalez, Woods and Eddins, Digital Image Processing using Matlab, 2nd Edition, Tata McGraw Hill 2
DIGITAL IMAGE PROCESSING Syllabus Module: 1 Digital Image fundamentals Image sampling and quantization relationship between pixels Intensity transformations and spatial filtering some basic intensity transformation functions, Histogram processing spatial filters for smoothing and sharpening 2D DFT and its properties Module: 2 basic filtering in the frequency domain image smoothing and sharpening Image Restoration and Reconstruction Image restoration/degradation model, noise models, restoration in the presence of noise only, estimating the degradation function Module:3 Color Image Processing: color models, Color transformation Wavelets and Multi-resolution Processing Image Compression: Fundamentals, Some basic compression methods Morphological Image Processing: Erosion and Dilation, opening and closing 3
What Is Digital Image Processing? DIP: Processing of digital images by means of a digital computer. An image may be defined as a two-dimensional function,f(x, y), where x and y are spatial coordinates, and the amplitude off at any pair of coordinates (x, y) is called the intensity or gray level of the image at that point. When x, y, and the amplitude values of f are all finite,discrete quantities, we call the image a digital image. Note that a digital image is composed of a finite number of elements, each of which has a particular location and value. These elements are referred to as picture elements, image elements, pels, and pixels. Pixel is the term most widely used to denote the elements of a digital image. 4
Why Image Processing? Improvement of pictorial information For Human Perception To make images more beautiful or understandable Automatic Perception of Image We call it Machine Vision, Computer Vision, Machine Perception, Computer Recognition For Storage and Transmission smaller, faster, more effective Image Processing for New Image Generation(New trends) Computer Graphics introduced Image Processing and Computer Vision technologies 5
History of Digital Image Processing Early 1920s: One of the first applications of digital imaging was in the newspaper industry The Bartlane cable picture transmission service Images were transferred by submarine cable between London and New York Pictures were coded for cable transfer and reconstructed at the receiving end on a telegraph printer 6
History of DIP (cont ) Mid to late 1920s: Improvements to the Bartlane system resulted in higher quality images New reproduction processes based on photographic techniques Increased number of tones in reproduced images Improved digital image Early 15 tone digital image 7
History of DIP (cont ) 1960s: Improvements in computing technology and the onset of the space race led to a surge of work in digital image processing 1964: Computers used to improve the quality of images of the moon taken by the Ranger 7 probe Such techniques were used in other space missions including the Apollo landings A picture of the moon taken by the Ranger 7 probe minutes before landing 8
History of DIP (cont ) 1970s: Digital image processing begins to be used in medical applications 1979: Sir Godfrey N. Hounsfield & Prof. Allan M. Cormack share the Nobel Prize in medicine for the invention of tomography, the technology behind Computerised Axial Tomography (CAT) scans Typical head slice CAT image 9
History of DIP (cont ) 1980s - Today: The use of digital image processing techniques has exploded and they are now used for all kinds of tasks in all kinds of areas Image enhancement/restoration Artistic effects Medical visualisation Industrial inspection Law enforcement Human computer interfaces 10
Fundamental steps in Digital Image Processing 11
Image Acquisition: An image is captured by a sensor (such as a monochrome or color TV camera) & digitized If the O/P of the camera or sensor is not already form, an ADC converter digitizes it.. Note that acquisition could be as simple as being given an image that is already in digital form. in digital 12
Image Enhancement: To bring out detail that is obscured, or simply to highlight certain features of interest in an image 13
Image Enhancement Examples (cont ) 14
Image Restoration Improving the appearance of an image Tend to be based on mathematical or probabilistic models of image degradation 15
Colour Image Processing Gaining in importance because of the significant increase in the use of digital images over the Internet Wavelets Foundation for representing images in various degrees of resolution Used in image data compression & pyramidal representation (images are subdivided successively into smaller Regions) 16
Morphological processing Deals with Tools for extracting image components that are useful in the representation & description of shape. 17
Segmentation Partitions an image into its constituent parts or objects Autonomous segmentation is one of the most difficult tasks in DIP A rugged segmentation procedure brings the process a long way toward successful solution of imaging problems that require objects to be identified individually O/P of the segmentation stage is raw pixel data, constituting either the boundary of a region or all the points in the region itself 18
Representation & Description Converts the raw data from segmentation to a form suitable for computer processing Representation -make a decision whether the data should be represented as a boundary or as a complete region 1. Boundary representation -focus on external shape characteristics, such as corners & inflections 2. Region representation -focus on internal properties, such as texture or skeleton shape Description(feature selection), deals with extracting attributes 19
Recognition & Interpretation Recognition : the process that assigns a label to an object based on the information provided by its Descriptors Interpretation : assigning meaning to an ensemble of recognized objects Knowledge Base A problem domain detailing regions of an image where the information of interest is known to be located Help to limit the search 20
Examples of Fields that Use Digital Image Processing The areas of application of digital image processing are so varied that some form of organization is desirable in attempting to capture the breadth of this field. Some Fields : Biometrics Medical imaging Factory Automation Remote sensing Documents image processing Defence/ Military Applications Photography Entertainment etc 21
Biometrics: Fingerprint recognition FBI s Integrated ion SystemAutomated Fingerprint Identificat IAFIS 22
Biometrics: Iris recognition 23
Extraction of settlement area from an aerial image 24
Earthquake Analysis from Space Image shows the ground displacement due to Landers earthquake in CA, 1992 25
Geographic Information Systems Digital image processing techniques are used extensively to manipulate satellite imagery Terrain classification Meteorology 26
Examples: Law Enforcement Image processing techniques are used extensively by law enforcers Number plate recognition for speed cameras/automated toll systems Fingerprint recognition Enhancement of CCTV images 27
Examples: HCI Try to make human computer interfaces more natural Face recognition Gesture recognition Does anyone remember the user interface from Minority Report? These tasks can be extremely difficult 28
Examples: Medicine Take slice from MRI scan of canine heart, and find boundaries between types of tissue Image with gray levels representing tissue density Use a suitable filter to highlight edges Original MRI Image of a Dog Heart Edge Detection Image 29
COMPONENTS OF A GENERAL-PURPOSE IMAGE PROCESSING SYSTEM 30
Image acquisition: This is carried out by sensors. Sensing involves 2 elements, namely Physical device that is sensitive to the energy radiated by the object we wish to image Digitizer that converts the o/p of the physical sensing device into digital form Specialized image processing hardware : consists of a digitizer & an ALU used for performing arithmetic or logical operations on the image. Also called front-end subsystem : Speed! Computer :is used for performing off line image processing tasks. Computer can range from a general PC to a super computer 31
Software: for image processing consists of specialized modules that perform specific tasks on the image, with options for users to write code. A well-designed package also includes the capability for the user to write code that, as a minimum, Sophisticated software packages allow the integration of those modules and general-purpose software commands from at least one computer language. Mass Storage : is essential in image processing applications Short Term Storage: required during processing. Frame Buffers that can store 1 or 2 images at a time & allows image zooming, scrolling &panning are used On Line Storage: for fast recall. Magnetic disks or optical media storage is used Archival Storage: for infrequent access. Magnetic tapes & optical disks are used 32
Image Displays : consists of monitors; they are driven by o/ps of image & graphic display cards. Sometimes stereo displays Hardcopy : devices for recording images include laser printers, film cameras, heat sensitive devices, inkjet units and digital units such as optical & CDROM disks Networking : is vital function, because it is necessary to transmit images. During transmission BW is the key factor to be considered Situation getting better with OFC and broadband communication 33
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