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Digital Image Processing
& Machine Vision
Instructed by

Dr. Abdul Rehman Abbasi
One picture is worth more than ten
thousa...
Course Contents
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.

(with estimated no. of lectures)

Introduction & Motivation (1)
Fundamenta...
Reference Books & Journals
•

Digital Image Processing
by Rafael C. Gonzalez & Richard E. Woods (2nd Edition), Pearson Edu...
Introduction to Image Processing
• An image is a 2-Dimensional function f(x,y) where x and y are
spatial coordinates, and ...
Image Function & Spatial Coordinates
Image Processing & the World
Motivation
 Medical Diagnosis
 Industrial Applications
 Security Applications
 Biometrics & Finance
 Seismic Analysis...
Medical Diagnosis

Digital Mammogram

MRI of Knee & Spine

Head CT Scan
Ultrasound
Industrial Applications
• Electronic Defect Detection

Product Testing/QA
Security Applications
Whole Body Scan

Vehicle Identification
Biometrics & Finance
Fingerprint Verification

Currency verification

Personnel Verification
Seismic Analysis
Mountains Ranges in Tibetan Plain

Seismic patterns showing oil
(natural resources) traps
Satellite Applications

Weather Forecast

Aerial Analysis
Space Explorations
Moon surface observation

North Pole observation
Imaging Spectrum
Images can work in a wide energy spectrum
Gamma Ray Imaging-1
• Nuclear Medicine
• Astronomical Observations
Gamma Ray Imaging-2
1.
2.

•

Inject a patient with a radioactive isotope that emits gamma rays as it
decays
Images are pr...
Imaging in Radio Band
Magnetic Resonance Imaging (MRI)
• Place a patient in a powerful magnet and passes radio waves throu...
Image Types
Some Common Image Formats and Their Characteristics
Format
•

jpg/jpeg (Joint Photographic Experts
Group)

•

Characterist...
Few Basic Image Operations
Contrast Enhancement
Image Resolution
Scaling
Rotation
Translate
Reflect or Mirroring
Image Sharpening
Sharpening
Image Sharpening
Machine Vision System Components
Components of a Generic Machine Vision System
• Radiation source: Illuminating the
object/scene
• Camera: The optical lens...
MV Schematic
Illumination + Camera + Sensor+ Signal
Processing Unit: Preprocessing
Processing Unit: Segmentation
Image Understanding: Tracking people’s activities
Image Understanding: Skin tracking
Image Understanding: Gesture Tracking
Comparison of Machine
&
Human Vision System
Human Vision versus Machine Vision Performance
Parameters
Functional Parameter

Human Vision

Machine Vision

Adaptability...
That’s All for this Session
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Digital Image Processing & Machine Vision Lecture 1 (Introduction & Motivation)

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  1. 1. Digital Image Processing & Machine Vision Instructed by Dr. Abdul Rehman Abbasi One picture is worth more than ten thousand words
  2. 2. Course Contents 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. (with estimated no. of lectures) Introduction & Motivation (1) Fundamental Concepts (1) Image Acquisition (1) Image Enhancement (2) Morphological Operations (1) Image Segmentation (3) Feature Extraction (3) Hardware & Software Methods in Image Processing (1) Advanced Research Areas in Image Processing (1) Mini-Project Presentation or Research Article Presentations (2)
  3. 3. Reference Books & Journals • Digital Image Processing by Rafael C. Gonzalez & Richard E. Woods (2nd Edition), Pearson Education • Digital Image Processing: A Practical Introduction using Java TM by Nick Efford, Pearson Education • Applied Image Processing by G.W. Awcock & R. Thomas , McGrawHill • Real-Time Image and Video Processing: From Research to Reality Nasser Kehtarnavaz and Mark Gamadia, Morgan & Claypool Publishers • • • • • Image & Vision Computing, Journal (IVC) Computer Vision & Image Understanding, Journal (CVIU) International Journal of Computer Vision (IJCV) IEEE Transactions on Pattern Analysis & Machine Intelligence (PAMI) IEEE Transactions on Image Processing
  4. 4. Introduction to Image Processing • An image is a 2-Dimensional function f(x,y) where x and y are spatial coordinates, and amplitude f at any pair of coordinates (x,y) is called the intensity or gray level of the image at that point. • When x,y, and f are finite and discrete we call it a digital image. • Digital image processing means processing/computing digital images using computational means such as using a digital computer.
  5. 5. Image Function & Spatial Coordinates
  6. 6. Image Processing & the World
  7. 7. Motivation  Medical Diagnosis  Industrial Applications  Security Applications  Biometrics & Finance  Seismic Analysis  Aerial Applications  Space Explorations
  8. 8. Medical Diagnosis Digital Mammogram MRI of Knee & Spine Head CT Scan Ultrasound
  9. 9. Industrial Applications • Electronic Defect Detection Product Testing/QA
  10. 10. Security Applications Whole Body Scan Vehicle Identification
  11. 11. Biometrics & Finance Fingerprint Verification Currency verification Personnel Verification
  12. 12. Seismic Analysis Mountains Ranges in Tibetan Plain Seismic patterns showing oil (natural resources) traps
  13. 13. Satellite Applications Weather Forecast Aerial Analysis
  14. 14. Space Explorations Moon surface observation North Pole observation
  15. 15. Imaging Spectrum Images can work in a wide energy spectrum
  16. 16. Gamma Ray Imaging-1 • Nuclear Medicine • Astronomical Observations
  17. 17. Gamma Ray Imaging-2 1. 2. • Inject a patient with a radioactive isotope that emits gamma rays as it decays Images are produced from the emissions collected by gamma ray detectors Positron Emission Tomography (PET)
  18. 18. Imaging in Radio Band Magnetic Resonance Imaging (MRI) • Place a patient in a powerful magnet and passes radio waves through his or her body in short pulses.
  19. 19. Image Types
  20. 20. Some Common Image Formats and Their Characteristics Format • jpg/jpeg (Joint Photographic Experts Group) • Characteristics • Image compression, supports 8-bit per color (RGB), generational degradation when edited repeatedly. tiff (Tagged-Image File Format) • Supports 8-bit and 16-bit per color , Support s OCR and device-specific color schemes • Gif (Graphics Interchange Format) • Limited to 256 colors , Supports animation • png (Portable Network Graphics) • 16 million colors (truecolor), Good for large images, best suited for editing • bmp (Bit Map) • Simple, suited for all WINDOWS applications, uncompressed
  21. 21. Few Basic Image Operations
  22. 22. Contrast Enhancement
  23. 23. Image Resolution
  24. 24. Scaling
  25. 25. Rotation
  26. 26. Translate
  27. 27. Reflect or Mirroring
  28. 28. Image Sharpening
  29. 29. Sharpening
  30. 30. Image Sharpening
  31. 31. Machine Vision System Components
  32. 32. Components of a Generic Machine Vision System • Radiation source: Illuminating the object/scene • Camera: The optical lens • Sensor: Converting the scene into a signal • Processer: Playing with the signal • Knowledge-Base: data understanding • Action unit: responding the visual information
  33. 33. MV Schematic
  34. 34. Illumination + Camera + Sensor+ Signal
  35. 35. Processing Unit: Preprocessing
  36. 36. Processing Unit: Segmentation
  37. 37. Image Understanding: Tracking people’s activities
  38. 38. Image Understanding: Skin tracking
  39. 39. Image Understanding: Gesture Tracking
  40. 40. Comparison of Machine & Human Vision System
  41. 41. Human Vision versus Machine Vision Performance Parameters Functional Parameter Human Vision Machine Vision Adaptability More adaptable to environmental conditions Not much adaptable to changing world Decision Making Humans are good in making relative comparisons Machine needs fixed numerical values to decide Consistency Human are tired and less consistent Machines are consistent Accuracy Accuracy is subjective Accuracy is higher Speed Human brain is fast in processing Machines with state of art have limited speed incomparable to human brain Spectrum Human can make use of only visible light (390-790mm) Machines can operate in Xray and infra red ranges
  42. 42. That’s All for this Session

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