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# Computer vision,,summer training programme

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### Computer vision,,summer training programme

1. 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. 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. 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. 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. 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