digital image processing (dip) dr. abdul basit siddiqui assistant professor-furc...
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Digital Image Processing (DIP)Dr. Abdul Basit Siddiqui
Assistant Professor-FURC
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Digital Image Processing (DIP)
Instructor Dr. Abdul Basit Siddiqui Text Book R. C. Gonzalez and R. E. Woods, “Digital Image
Processing, Pearson Education, Inc., 2002. Prerequisites 1. Fundamental knowledge of probability and
random variables, Vectors and Matrices. 2. Working knowledge of Matlab 3. DSP topics such as convolution, FFT,
filtering, etc.
Yahoo Group Lectures and Assignments will be updated on yahoo group regularly.
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Grading Policy
Attendance 05%
Assignments 05%
Quizzes 05%
Project 05%
Midterm 30%
Final 50%
History
• 1921: Image transmission
– Newspaper industry– Cable transmission– London – New York
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History
• 1960’s: Space program
– Moon picture– Enhancement by
computer • 1970: Computerized
tomography (CT)
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• The first picture of the moon 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
Image Processing Applications– Nuclear medicine– Medical Diagnostics– Automated Industrial Inspection– Remote Sensing
• Weather Prediction• Military reconnaissance
– 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 ExamplesPhoto Restoration
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Image Processing Examples
Photo Colorization
Original B/W Image Colorized Image Original Image Colorized Image
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Image Processing Examples
Photo Colorization
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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 ExamplesStereo 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 ExamplesFace Detection
Image shows the ground displacement of a typical area due to earthquake
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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 ExamplesFace Morphing
Faulty Image of Saturn Recovered Image
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 Imaging– Gamma 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
– Some Research ProjectsSome Research Projects
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Monitoring Human Behavior from Video Taken 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: Source: http://server.cs.ucf.edu/~vision/http://server.cs.ucf.edu/~vision/
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EM Spectrum
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Applications of DIP (EM Band Imaging)
Gamma-Ray Imaging
– Nuclear medicine, astronomical observations.
X-Ray Imaging– Medical diagnostics (CAT scans, x-ray scans), industry, astronomy.
Ultra-Violet Imaging
– Fluorescence 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
MONITORING HEAD/EYE MOTION FOR DRIVER ALERTNESS
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MONITORING FAST FOOD PRODUCTION
• 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 employee performance and food safety inspection.
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Classification of DIP and Computer Vision Processes
Low-Level Process: (DIP)
– Primitive operations where inputs and outputs are images; major functions: 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
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Image Processing Steps
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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 Restoration– Noise reduction techniques
– Geometric transformations
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DIP Course
Color Image Processing– Color models
– Pseudocolor image processing
– Color transformations and color segmentation
Wavelets and Multi-Resolution Processing
– Multi-resolution expansion
– Wavelet transforms, etc.
Image Compression
– Image compression models
– Error free compression
– Lossy compression, etc
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DIP Course
Image Segmentation
– Edge, point and boundary detection
– Thresholding
– Region based segmentation, etc
Image Representation
• Image– Two-dimensional function f(x,y)– x, y : spatial coordinates
• Value of f : Intensity or gray level
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Digital Image
• A set of pixels (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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