Computer vision,,summer training programme
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This document outlines the topics covered in a course on computer vision and image processing using MATLAB. The course covers fundamentals of MATLAB, image processing techniques, thumb detection, fingerprint matching and project development. Specific topics include image types in MATLAB, image arithmetic, filtering, transforms, segmentation, texture analysis, noise removal, and compression. Morphology, discrete transforms, and color image processing are also discussed.
Computer vision,,summer training programme
- 1. Add: C-32,Beside Nirula’sHotel,SEC-2NOIDA Near sec-15 Metro (08587849630) LGF 11/12,Narayan Plaza Near Domino’s,Engineeringcollege chauraha,,Lucknow (09807507429) Computer Vision & Image Processing with MATLAB Covers basics of MATLAB, GUI programming, Image Processing Techniques, Thumb Detection System, Finger Print Matching and Project Development Introduction MATLAB Fundamentals MATLAB for Data Processing and Visualization MATLAB Programming Techniques MATLAB for Building Graphical User Interfaces Simulink for System and Algorithm Modeling Graphics in MATLAB, MATLAB Toolboxes, Data Acquisition with MATLAB Interfacing MATLAB with C code, Deploying MATLAB Based applications Part I Introduction to Image Processing Images in MATLAB - Binary, Indexed, Grayscale, Truecolor Images Image Coordinate Systems: Pixel & Spatial Coordinates Converting Between Image Types and Classes Simple Image Arithmetic Reading and Writing Images Improve Image Contrast Analyzing Images - Read Image Use Morphological Opening to Estimate the Background Increase the Image Contrast Threshold the Image Identify Objects in the Image Create Histogram of the Area Using the Image Tool to Explore Images
- 2. Add: C-32,Beside Nirula’sHotel,SEC-2NOIDA Near sec-15 Metro (08587849630) LGF 11/12,Narayan Plaza Near Domino’s,Engineeringcollege chauraha,,Lucknow (09807507429) Using Image Tool Navigation Aids Getting Information about the Pixels in an Image Getting Information About an Image Using the Image Information Tool Viewing Image Sequences Part II Sampling & Quantization Introduction to terms Isopreference Curves Non-Uniform Sampling Point-Spread Function (PSF) Physical Resolution Image Enhancement in the Spatial Domain Spatial Domain Methods Convolution & Correlation Point Processing Neighborhood Processing Low-Pass Filtering (Smoothing) Salt and Pepper Noise Filtering Low-Pass Averaging Filter Low-Pass Median Filtering High-Pass Filtering High-Boost Filtering Filtering an Image with Predefined Filter Types Zooming, Replication & Linear Interpolation Resizing, Rotating,Cropping an Image Performing General 2-D Spatial Transformations
- 3. Add: C-32,Beside Nirula’sHotel,SEC-2NOIDA Near sec-15 Metro (08587849630) LGF 11/12,Narayan Plaza Near Domino’s,Engineeringcollege chauraha,,Lucknow (09807507429) Part III Image Registration Registering an Image Using Normalized Cross-Correlation Image Enhancement Based on Histogram Modelling Linear Stretching Histogram Equalisation Histogram Specification Part IV Image Enhancement in the Frequency Domain The Fourier Transform 1-D Fourier Transform 2-D Fourier Transform Discrete Fourier Transform (DFT) Low-Pass Frequency Domain Filters Ideal Low-Pass Filter Butterworth Low-Pass Filter Gaussian Low-Pass Filter High-Pass Frequency Domain Filters Ideal High-Pass Filters Butterworth High-Pass Filter Gaussian High-Pass Filter Homomorphic Filtering Relationship Between Filtering in Spatial and Frequency Domains Part V Image Segmentation Point, Line & Edge Detection
- 4. Add: C-32,Beside Nirula’sHotel,SEC-2NOIDA Near sec-15 Metro (08587849630) LGF 11/12,Narayan Plaza Near Domino’s,Engineeringcollege chauraha,,Lucknow (09807507429) Region Of Interest(ROI) - Based Processing Specifying a Region of Interest Filtering & Filling a ROI Analyzing and Enhancing Images Getting Information about Image Pixel Values and Image Statistics Analyzing Images Analyzing the Texture of an Image Adjusting Pixel Intensity Values Removing Noise from Images Getting Information about Image Pixel Values and Image Statistics Creating an Intensity Profile of an Image Using improfile Displaying a Contour Plot of Image Data Creating an Image Histogram Detecting Edges Using the edge Function Tracing Object Boundaries in an Image Detecting Lines Using the Hough Transform Analyzing Image Homogeneity Using Quadtree Decomposition Part VI Analyzing the Texture of an Image Understanding Texture Analysis Using Texture Filter Functions Using a Gray-Level Co-Occurrence Matrix (GLCM) Adjusting Pixel Intensity Values Understanding Intensity Adjustment Adjusting Intensity Values to a Specified Range Adjusting Intensity Values Using Histogram Equalization
- 5. Add: C-32,Beside Nirula’sHotel,SEC-2NOIDA Near sec-15 Metro (08587849630) LGF 11/12,Narayan Plaza Near Domino’s,Engineeringcollege chauraha,,Lucknow (09807507429) Removing Noise from Images Removing Noise By Linear Filtering Removing Noise By Median Filtering Removing Noise By Adaptive Filtering Image Deblurring Understanding Deblurring Deblurring with the Wiener Filter Part VII Morphology Representation and Description Discrete Image Transforms Image Compression Wavelet Transforms Colour Image Processing