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Digital Image Processing (DIP)

Dr. Abdul Basit Siddiqui

Assistant Professor-FUIEMS

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Grading Policy

Assignments 05%

Quizzes 05%

Attendance 05%

Midterm 30%

Project 05%

Final 50%

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History

1960s: Space program

Moon picture

Enhancement by

computer

1970: Computerized

tomography (CT)

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The first picture of themoon by a U.S.

spacecraft on July

31,1964 at 9:09 A.M.

(courtesy of NASA)

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Why Do We Process Images?

Facilitate picture storage and transmission

Efficiently store an image in a digital camera

Send an image through mobile phone

Enhance and restore images

Remove scratches from an old photo

Improve visibility of tumor in a radiograph

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Why Do We Process Images?

Extract information from images

Measure water pollution from aerial images

Measure the 3D distances and heights of objects from

stereo images

Prepare for display or printing

Adjust image size

Halftoning

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Image Processing Applications

Nuclear medicine

Medical Diagnostics

Automated Industrial Inspection

Remote Sensing

Weather Prediction

Military Investigations Geological exploration

Astronomical Observations

Image database management

The paperless office

Photographers, advertising agencies and publishers

Machine vision Biometrics

Finger Prints

Iris etc.

Movies and entertainment

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Image Enhancement

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Image Processing Examples

Photo Restoration

Damaged Image Restored Image

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Image Processing Examples

Photo Restoration

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Image Processing Examples

Original Images Enhanced Images

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Image Processing Examples

Restoration of Image from Hubble Space Telescope

Faulty Image of Saturn Recovered Image

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Image Processing Examples

Halftoning

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Image Processing Examples

Halftoning

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Image Processing Examples

Halftoning

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Image Processing Examples

Extraction of Settlement Area from an Aerial image

Faulty Image of Saturn Recovered Image

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Image Processing Examples

Earthquake Analysis from Space

Image shows the ground displacement of a typical area due to earthquake

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Image Processing Examples

Stereo Images from Satellite

Image shows the ground displacement of a typical area due to earthquake

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Image Processing Examples

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Image Processing Examples

Face Tracking

Image shows the ground displacement of a typical area due to earthquake

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Image Processing Examples

Face Morphing

Faulty Image of Saturn Recovered Image

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Image Morphing

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Image Processing Examples

Fingerprint Recognition

Faulty Image of Saturn Recovered Image

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Applications of DIP

Electromagnetic (EM) band ImagingGamma ray band images

X-ray band images

Ultra-violet band images

Visual light and infra-red images

Imaging based on micro-waves and radio waves

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Some Research Projects

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Monitoring Human Behavior from VideoTaken in an Office Environment

A system which makes context-based

decisions about the actions of people in a

room. These actions include entering,using a computer terminal, opening a

cabinet, picking up a phone, etc.

Source:http://server.cs.ucf.edu/~vision/

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http://server.cs.ucf.edu/~vision/projects/Office/IVC.pdfhttp://server.cs.ucf.edu/~vision/projects/Office/IVC.pdfhttp://server.cs.ucf.edu/~vision/projects/Office/IVC.pdfhttp://server.cs.ucf.edu/~vision/projects/Office/IVC.pdf

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EM Spectrum

li i f d i

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Applications of DIP (EM Band Imaging)

Gamma-Ray ImagingNuclear medicine, astronomical observations.

X-Ray Imaging

Medical diagnostics (CAT scans, x-ray scans), industry, astronomy.

Ultra-Violet ImagingFluorescence microscopy, astronomy

Visible & Infrared-band Imaging (most widely used)

Light microscopy, astronomy, remote sensing, industry, law

enforcement, military recognizance, etc.

Micro-wave and Radio band Imagery

Radar, Medicine (MRI), astronomy

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MONITORING HEAD/EYE MOTIONFOR DRIVER ALERTNESS

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MONITORING FAST FOODPRODUCTION

The purpose of the project

is to automatically monitor a

fast food employee as she

puts together a sandwich.Helpful in determining

correctness of sandwich

assembly, collecting

statistics on employeeperformance and food

safety inspection.

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Cl ifi i f DIP d C Vi i P

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Classification of DIP and Computer Vision Processes

Low-Level Process: (DIP)

Primitive operations where inputs and outputs are images; majorfunctions: image pre-processing like noise reduction, contrast

enhancement, image sharpening, etc.

Mid-Level Process (DIP and Computer Vision)

Inputs are images, outputs are attributes (e.g., edges); major

functions: segmentation, description, classification / recognition of

objects

High-Level Process (Computer Vision)

Make sense of an ensemble of recognized objects; perform the

cognitive functions normally associated with vision

I P i S

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Image Processing Steps

DIP C

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DIP Course

Digital Image Fundamentals and Image Acquisition(briefly)

Image Enhancement in Spatial Domain

Pixel operations

Histogram processing

Filtering

Image Enhancement in Frequency Domain

Transformation and reverse transformation

Frequency domain filters

Homomorphic filtering

Image RestorationNoise reduction techniques

Geometric transformations

DIP C

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DIP Course

Color Image ProcessingColor models

Pseudocolor image processing

Color transformations and color segmentation

Wavelets and Multi-Resolution Processing

Multi-resolution expansion

Wavelet transforms, etc.

Image Compression

Image compression modelsError free compression

Lossy compression, etc

DIP C

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DIP Course

Image Segmentation

Edge, point and boundary detection

Thresholding

Region based segmentation, etc

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Image Representation

Image

Two-dimensional function f(x,y)

x, y: spatial coordinates

Value off: Intensity orgray level

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Digital Image

A set ofpixels (picture elements, pels)

Pixel means

pixel coordinate

pixel value

or both

Both coordinates and value are discrete

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Example

640 x 480 8-bit image

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