Lecture 1
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This document outlines the organizational details and syllabus for the CS-467 Image Processing and Computer Vision course offered in the fall of 2015. The class will meet on Thursdays from 1:00-3:45 pm in room SCIT215 and be instructed by Dr. Igor Aizenberg. Students will complete projects involving digital image processing techniques and present written reports and results. The final grade will be calculated as the average of project grades using the standard grading scale. Topics covered will include image enhancement, filtering, color processing, and introduction to image recognition.
Lecture 1
- 1. CS-467 Image Processing and Computer Vision Fall 2015 1
- 2. Organizational Details Class Meeting: 1:00pm-3:45pm; Thursday; Room SCIT215 Instructor: Dr. Igor Aizenberg Office: Science and Technology Building, 104C Phone 903-334 6654 e-mail: igor.aizenberg@tamut.edu Office hours: Tuesday 12:30a-2:30p; Thursday 11:00a-1:00p Class Web Page: http://www.eagle.tamut.edu/faculty/igor/CS-467.htm 2
- 3. Text Book (optional) • R. C. Gonzalez and R. E. Woods, Digital image Processing, 3rd Edition, • ISBN-10: 013168728X • ISBN-13: 9780131687288 • Prentice Hall, Copyright: 2008 • Published: 08/21/2007. 3
- 4. Evaluation • Projects will be given frequently throughout the semester. • Students will be required not only to learn the methods studied in class, but also have to implement them. • Each project must be defended by presenting a written report (prepared in MS-Word) demonstrating the corresponding processing results ( the resulting images and/or source code shall also be presented). Each project is usually due a week after it has been assigned. 4
- 5. Grading Grading Method Each project will be graded and the final grade will be the average over all the projects grades. Grading Scale: 90%+ A 80%+ B 70%+ C 60%+ D less than 60% F 5
- 6. What is Digital Image Processing? What is Computer Vision? • Digital Image Processing refers to processing digital images by means of a digital computer. • Computer Vision refers to deep image analysis, recognition of objects located in digital images and to simulation of the cognitive functions normally associated with vision. 6
- 7. What is Digital Image Processing? What is Computer Vision? • There is no some well-defined border between high-level image processing (image segmentation, objects detection, and recognition of individual objects) and low- level computer vision (objects ensemble recognition) 7
- 8. What we will study? • Visual Perception. Light and Electromagnetic Spectrum. Image Acquisition, Sampling, and Quantization • Image Enhancement in the Spatial Domain (noise models, noise filtering, linear and nonlinear filters, image sharpening, edge detection) • Image Enhancement in the Frequency Domain (Fourier transform, periodic and quasi-periodic noise filtering, restoration of blurred images) • Processing of Color Images • Introduction to Image Recognition 8
- 9. What is a digital image? • In fact, all natural images are analog (in terms of signal processing) , continuous (in terms of mathematics) and generally infinite. • Digital images are discrete and finite. They are composed from a finite number of elements, each of which has a particular location (coordinates) and value (intensity value). These elements are called pixels. 9
- 10. Digital Image • Mathematically, a digital image can be considered as a discrete function • is a finite domain (which is called a spatial domain) of the image-function, and I is a co- domain of the image-function 10 ( ) { } { }2 , : ; 0,1,2,..., 1 , 0,1,..., 1f x y D I D N I k→ = − = − 2 D
- 11. Digital Image • A graphical representation of the function results in visualized digital image, the corresponding points with their values located according to their spatial coordinates x, y are nothing else than pixels. • A digital image with has maximum k gray levels. 0 is black, k-1 is white. All values between them are “gray” with the different tints. Such images are commonly referred to as gray-scale. 11 ( ),f x y { }0,1,..., 1I k= −
- 12. Color Digital Image • Color digital images consist of 3 or 4 “gray” channels (depending on the color space). • The most popular space is RGB (red, green, and blue) ,where each of channels taken separately is a gray-scale digital image in terms of our definition. 12
- 13. Historical Observation © 1992-2008 R.C. Gonzalez & R.E. Woods First digital images with 5 gray levels (1921-1922) 13
- 14. © 1992-2008 R.C. Gonzalez & R.E. Woods Historical Observation Digital image with 15 gray levels (1929) 14
- 15. Historical Observation Digital image with 256 gray levels (1964) © 1992-2008 R.C. Gonzalez & R.E. Woods 15
- 16. Areas of Application of Digital Image Processing • Aerospace Imaging • Medical Imaging • Digital Photography • Surveillance Systems • Security and Intelligence • Nondestructive Check • Remote Sensing 16
- 17. Sources of Digital Images • Digital images can be categorized according to their source (visual, X-ray, Infrared, ultraviolet, ultrasound, etc.) • The energy sources for images are: electromagnetic energy spectrum, acoustic, ultrasonic, electronic • Images based on radiation from the electromagnetic spectrum are the most frequently appeared 17
- 18. Electromagnetic Spectrum • Electromagnetic waves are on the one hand sinusoidal waves of varying wavelengths and on the other hand they are streams of massless particles, each travelling in a wavelike pattern and moving at the speed of light. • Each massless particle contains a certain amount (bundle) of energy, which is called a photon. © 1992-2008 R.C. Gonzalez & R.E. Woods 18
- 20. Gamma-Ray Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 20
- 21. X-Ray Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 21
- 22. © 1992-2008 R.C. Gonzalez & R.E. Woods Ultraviolet Imaging 22 (a) and (b) - Fluorescent Microscopy Images
- 23. Light Microscopy Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 23
- 24. Multispectral Satellite Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 24
- 25. Multispectral Satellite Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 25
- 26. Satellite Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 26
- 27. Infrared Satellite Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 27
- 28. Infrared Satellite Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 28
- 29. Nondestructive Check Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 29
- 30. Visual Spectrum Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 30
- 31. Synthetic Radar Satellite Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 31
- 32. MRI Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 32
- 33. Multispectral Astronomy Imaging © 1992-2008 R.C. Gonzalez & R.E. Woods 33
- 34. © 1992-2008 R.C. Gonzalez & R.E. Woods Remote Sensing Imaging 34
- 35. © 1992-2008 R.C. Gonzalez & R.E. Woods Ultrasound Medical Imaging 35
- 36. © 1992-2008 R.C. Gonzalez & R.E. Woods Scanning Electron Microscope Imaging 36
- 38. © 1992-2008 R.C. Gonzalez & R.E. Woods Basic Image Processing Methods 38
- 39. © 1992-2008 R.C. Gonzalez & R.E. Woods Components of Digital Image Processing System 39