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