Dip lect1-sent
-
Upload
abdul-abbasi -
Category
Education
-
view
72 -
download
0
Transcript of Dip lect1-sent
One picture is worth more than ten thousand words
Digital Image Processing & Machine Vision
Instructed by
Dr. Abdul Rehman Abbasi
Course Contents (with estimated no. of lectures)
1. Introduction & Motivation (1)2. Fundamental Concepts (1)3. Image Acquisition (1)4. Image Enhancement (2)5. Morphological Operations (1)6. Image Segmentation (3)7. Feature Extraction (3)8. Hardware & Software Methods in Image Processing (1)9. Advanced Research Areas in Image Processing (1)10. Mini-Project Presentation or Research Article Presentations (2)
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
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.
Image Function & Spatial Coordinates
Image Processing & the World
Motivation
Medical Diagnosis Industrial ApplicationsSecurity ApplicationsBiometrics & FinanceSeismic Analysis Aerial ApplicationsSpace Explorations
Medical Diagnosis
Digital Mammogram
Head CT Scan
MRI of Knee & Spine
Ultrasound
Industrial Applications
• Electronic Defect Detection
Product Testing/QA
Security ApplicationsWhole Body Scan Vehicle Identification
Biometrics & Finance
Fingerprint Verification Currency verification
Personnel Verification
Seismic Analysis
Seismic patterns showing oil(natural resources) traps
Mountains Ranges in Tibetan Plain
Satellite Applications
Weather Forecast Aerial Analysis
Space Explorations
North Pole observation
Moon surface observation
Imaging Spectrum
Images can work in a wide energy spectrum
Gamma Ray Imaging-1
• Nuclear Medicine • Astronomical Observations
Gamma Ray Imaging-2
1. Inject a patient with a radioactive isotope that emits gamma rays as it decays
2. Images are produced from the emissions collected by gamma ray detectors
• Positron Emission Tomography (PET)
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.
Image Types
Some Common Image Formats and Their Characteristics
Format• jpg/jpeg (Joint Photographic Experts
Group)
• tiff (Tagged-Image File Format)
• Gif (Graphics Interchange Format)
• png (Portable Network Graphics)
• bmp (Bit Map)
Characteristics • Image compression, supports 8-bit per color
(RGB), generational degradation when edited repeatedly.
• Supports 8-bit and 16-bit per color , Support s OCR and device-specific color schemes
• Limited to 256 colors , Supports animation
• 16 million colors (truecolor), Good for large images, best suited for editing
• Simple, suited for all WINDOWS applications, uncompressed
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• Sensor: Converting the scene into a signal• Processer: Playing with the signal• Knowledge-Base: data understanding• Action unit: responding the visual information
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 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 X-ray and infra red ranges
That’s All for this Session