MEPP 432
Image Processing and Analysis
3 Cr.
Course objectives:
The course is designed to provide fundamental knowledge necessary to understand elementary principles of image processing and analyses andalsosubjected to research trends and applications. This course basically deals with main principles of digital image acquisition, processing, and analyses - illustrated with examples using a commonly used software tool MATLAB.
Course Plan
Introduction to Image Processing & Analysis:
Overview, Human Vision, Images and Pictures, Computer Vision, Image Processing and Applications, Image Acquisition and Sampling, Image Types and File I/O, Image Properties.
Familiarization to MATLAB® Environment:
Background, Applications, MATLAB Desktop, MATLAB Help, Useful Commands and Functions, Mathematical Operators.
Matrix Manipulation in MATLAB:
Preview, Data Representation, Matrix Notation, Matrix Indices, Generating Matrices, Matrix Concatenation, Deleting Rows & Columns, Matrix Properties, Functions.
Image Processing in MATLAB:
Pixel Coordinates, Image Representation, Image Format, Image Loading, Displaying and Saving, Image Information, Pixel Information, Image Type Conversions, Geometric Operations, Arithmetic Operations, Image Transform.
Image Analysis:
Image Enhancement in Spatial Domain – Basic Gray Level Transformation, Histogram Processing, Spatial Operations (Filtering); Image Enhancement in Frequency Domain – Fourier Transform; Features Extraction and Representations.
Image Segmentation:
Similarity and Discontinuity Based Techniques, Thresholding, Point Detection, Line Detection, Edge Detection, Detection of discontinuities, Region Oriented Segmentation.
Case Studies:
Application of Image Processing to Solve Real-World Problems in Several Areas Including Thermal Imaging, R&D, Industry, Medical, Remote Sensing, Surveillance, etc.
References
1. Umbaugh, Scott E. Digital Image Processing and Analysis: Applications with MATLAB and CVIPtools. CRC Press, 2017.
2. Solomon, Chris, and Toby Breckon. Fundamentals of Digital Image Processing: A practical approach with examples in Matlab. John Wiley & Sons, 2011.
3. Qidwai, Uvais, and Chi-hau Chen. Digital image processing: an algorithmic approach with MATLAB. CRC press, 2009.