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