Digital Image Processing: Introduction
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1 Digital : Introduction Slides by Brian Mac Namee [email protected] Materials found at: Slides: Lectures: Course Website:
2 2 References Digital, Rafael C. Gonzalez & Richard E. Woods, Addison-Wesley, 2002 Much the material that follows is taken from this book Machine Vision: Automated Visual Inspection and Robot Vision, David Vernon, Prentice Hall, 1991 Available online at: homepages.inf.ed.ac.uk/rbf/books/vernon/
3 3 Contents This lecture will cover: What is a digital image? What is digital image processing? History digital image processing State the art examples digital image processing Key stages in digital image processing
4 s taken from Gonzalez & Woods, Digital (2002) 4 What is a Digital? A digital image is a representation a twodimensional image as a finite set digital values, called picture elements or pixels
5 s taken from Gonzalez & Woods, Digital (2002) 5 What is a Digital? (cont ) Pixel values typically represent gray levels, colours, heights, opacities etc Remember digitization implies that a digital image is an approximation a real scene 1 pixel
6 6 What is a Digital? (cont ) Common image formats include: 1 sample per point (B&W or Grayscale) 3 samples per point (Red, Green, and Blue) 4 samples per point (Red, Green, Blue, and Alpha, a.k.a. Opacity) For most this course we will focus on grey-scale images
7 7 What is Digital? Digital image processing focuses on two major tasks Improvement pictorial information for human interpretation image data for storage, transmission and representation for autonomous machine perception Some argument about where image processing ends and fields such as image analysis and computer vision start
8 8 What is DIP? (cont ) The continuum from image processing to computer vision can be broken up into low-, mid- and high-level processes Low Level Process Input: Output: Examples: Noise removal, image sharpening Mid Level Process Input: Output: Attributes Examples: Object recognition, segmentation High Level Process Input: Attributes Output: Understanding Examples: Scene understanding, autonomous navigation In this course we will stop here
9 s taken from Gonzalez & Woods, Digital (2002) 9 History Digital Early 1920s: One the first applications digital imaging was in the newspaper industry The Bartlane cable picture transmission service Early digital image s 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
10 s taken from Gonzalez & Woods, Digital (2002) 10 History 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 tones in reproduced images Improved digital image Early 15 tone digital image
11 s taken from Gonzalez & Woods, Digital (2002) 11 History DIP (cont ) 1960s: Improvements in computing technology and the onset the space race led to a surge work in digital image processing 1964: Computers used to improve the quality images the moon taken by the Ranger 7 probe Such techniques were used in other space missions including the Apollo landings A picture the moon taken by the Ranger 7 probe minutes before landing
12 s taken from Gonzalez & Woods, Digital (2002) 12 History DIP (cont ) 1970s: Digital image processing begins to be used in medical applications 1979: Sir Godfrey N. Hounsfield & Pr. Allan M. Cormack share the Nobel Prize in medicine for the invention tomography, the technology behind Computerised Axial Tomography (CAT) scans Typical head slice CAT image
13 13 History DIP (cont ) 1980s - Today: The use digital image processing techniques has exploded and they are now used for all kinds tasks in all kinds areas enhancement/restoration Artistic effects Medical visualisation Industrial inspection Law enforcement Human computer interfaces
14 s taken from Gonzalez & Woods, Digital (2002) 14 Examples: Enhancement One the most common uses DIP techniques: improve quality, remove noise etc
15 15 Examples: The Hubble Telescope Launched in 1990 the Hubble telescope can take images very distant objects However, an incorrect mirror made many Hubble s images useless processing techniques were used to fix this
16 16 Examples: Artistic Effects Artistic effects are used to make images more visually appealing, to add special effects and to make composite images
17 s taken from Gonzalez & Woods, Digital (2002) 17 Examples: Medicine Take slice from MRI scan canine heart, and find boundaries between types tissue with gray levels representing tissue density Use a suitable filter to highlight edges Original MRI a Dog Heart Edge Detection
18 s taken from Gonzalez & Woods, Digital (2002) 18 Examples: GIS Geographic Information Systems Digital image processing techniques are used extensively to manipulate satellite imagery Terrain classification Meteorology
19 s taken from Gonzalez & Woods, Digital (2002) 19 Examples: GIS (cont ) Night-Time Lights the World data set Global inventory human settlement Not hard to imagine the kind analysis that might be done using this data
20 s taken from Gonzalez & Woods, Digital (2002) 20 Examples: Industrial Inspection Human operators are expensive, slow and unreliable Make machines do the job instead Industrial vision systems are used in all kinds industries Can we trust them?
21 21 Examples: PCB Inspection Printed Circuit Board (PCB) inspection Machine inspection is used to determine that all components are present and that all solder joints are acceptable Both conventional imaging and x-ray imaging are used
22 s taken from Gonzalez & Woods, Digital (2002) 22 Examples: Law Enforcement processing techniques are used extensively by law enforcers Number plate recognition for speed cameras/automated toll systems Fingerprint recognition Enhancement CCTV images
23 23 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
24 24 Key Stages in Digital Restoration Morphological Enhancement Segmentation Acquisition Object Recognition Problem Domain Colour Compression Representation & Description
25 s taken from Gonzalez & Woods, Digital (2002) 25 Key Stages in Digital : Aquisition Restoration Morphological Enhancement Segmentation Acquisition Object Recognition Problem Domain Colour Compression Representation & Description
26 s taken from Gonzalez & Woods, Digital (2002) 26 Key Stages in Digital : Enhancement Restoration Morphological Enhancement Segmentation Acquisition Object Recognition Problem Domain Colour Compression Representation & Description
27 s taken from Gonzalez & Woods, Digital (2002) 27 Key Stages in Digital : Restoration Restoration Morphological Enhancement Segmentation Acquisition Object Recognition Problem Domain Colour Compression Representation & Description
28 s taken from Gonzalez & Woods, Digital (2002) 28 Key Stages in Digital : Morphological Restoration Morphological Enhancement Segmentation Acquisition Object Recognition Problem Domain Colour Compression Representation & Description
29 s taken from Gonzalez & Woods, Digital (2002) 29 Key Stages in Digital : Segmentation Restoration Morphological Enhancement Segmentation Acquisition Object Recognition Problem Domain Colour Compression Representation & Description
30 s taken from Gonzalez & Woods, Digital (2002) 30 Key Stages in Digital : Object Recognition Restoration Morphological Enhancement Segmentation Acquisition Object Recognition Problem Domain Colour Compression Representation & Description
31 s taken from Gonzalez & Woods, Digital (2002) 31 Key Stages in Digital : Representation & Description Restoration Morphological Enhancement Segmentation Acquisition Object Recognition Problem Domain Colour Compression Representation & Description
32 32 Key Stages in Digital : Compression Restoration Morphological Enhancement Segmentation Acquisition Object Recognition Problem Domain Colour Compression Representation & Description
33 33 Key Stages in Digital : Colour Restoration Morphological Enhancement Segmentation Acquisition Object Recognition Problem Domain Colour Compression Representation & Description
34 34 Summary We have looked at: What is a digital image? What is digital image processing? History digital image processing State the art examples digital image processing Key stages in digital image processing Next time we will start to see how it all works
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