Image Processing

Register for free….Limited period OFFER. Digital Image Processing is a rapidly evolving field with growing applications in science and engineering. Image processing holds the possibility of developing the ultimate machine that could perform the visual functions of all living beings. There is an abundance of image processing applications that can serve mankind with the available and anticipated technology in the near future. The syllabus is competent with master degree. Learners will get insight of each topic. The course includes study material with Question and Answers.

Books :

1) R. C. Gonsales R. E. Woods, “Digital Image Processing”,Second Edition, Person Eduction.

2) Anil K. Jain, “Fundamentals of Image Processing”, PHI.

Course Information

Tracks: Image Processing

Categories: Bachelor of Engineering : CS and IT, BCA, MCA, ME, Msc Computer Science, MSc IT

Tags: BE Image Processing, Image Processing, ME Image Processing, MSc Computer Science, MSc Computer Science Image Processing, MSc IT, MSc IT Image Processing

Course Instructor

Dr. Mahendra Kanojia Author

Dr. Mahendra Kanojia M.Phil., Ph.D. (Computer Science) Currently employed as HOD of the Department of Computer Science and Head of the Computer Education Centre in Sheth L.U.J. and Sir M.V. College, Mumbai , India. Dr. Mahendra completed his Ph.D. and M.Phil in Computer Science from India. He is the founder of the e-learning website, www.rocktheit.com. He has more than 11 years of academic experience at college and university level. He holds an expert role in research, software training and software consulting. He is also a faculty member of Vissanji Academy International School, Mumbai , India, as a computer application teacher. He is actively interested in teaching master’s students and has been affiliated with more than 18 colleges as a visiting faculty offering master’s degrees in Mumbai , India. With his self-designed approach to training newbies in research and development, he has been mentoring a variety of research-based projects at PG and UG level. Dr. Mahendra is also a technical reviewer at the ISDA and SoCPAR International Research Conferences. Dr. Mahendra ‘s deep interest in research is evident from his list of publications. He was designated chair of the examination for M.Sc. IT IDOL, Mumbai University. He served on the B.Sc. Theory and Practical Examination Committees. Computer Science, University of Mumbai as a board member, paper setter, moderator, inspector and examiner. Dr. Mahendra is also in charge of the various college committees. Dr. Mahendra’s research focuses on the detection of cancer using machine learning and deep learning techniques. He is also interested in the paradigm of medical diagnosis using digital image processing and AI approaches. He is exploring the field of data science and data analytics after receiving his PhD in Computer Science on Breast cancer detection using deep learning methods. Studies of IoT and chatbots are also part of his current projects. He is emerging as a multidisciplinary computer science research scientist. Dr. Mahendra principally believes that : “If humans can, technology can”.

FREE

1 year of access

Theory

Fundamentals of Digital Image

Introduction Image Processing, Types of Image Processing, Types of Digital Image, Fundamental Steps in Digital Image Processing, Components of an Image Processing System,

Digital Image Processing Systems

Structure Of Human Eye, Image Formation In The Human Eye, Brightness Adaptation And Discrimination, Image Sensing And Acquisition, A Simple Image Formation Model, Image Sampling And Quantization, Representing Digital Image, Spatial and Gray-Level Resolution

Image Enhancement in The Spatial Domain

Introduction, Basic Grey Level Transform, Identity Transform Function, Image Negatives, Logarithmic Functions, Power-Law Functions, Piecewise-Linear Transformation Functions, Image Contrast Stretching, Image Thresholding, Gray-level Slicing, Bit-plane Slicing, Basics of Histogram Processing, Histogram equalisation (Automatic), Histogram matching (specification), Local histogram equalisation, Enhancement using Arithmetic/ Logic Operation

Image Filtering in the Spatial Domain

Various Types of Image Noise, Fundamentals of Spatial Filtering, Spatial Masks, Spatial Convolution and Correlation, Smoothing Spatial Filters, Sharpening Spatial Filters (High Pass), Combining Spatial Enhancement Methods

Fourier Series And Transform In Digital Image Processing

Background, Impulse Function and its Properties, The Fourier Transform , One Dimensional Fourier Transform, Two Dimensional Fourier Transform, One Dimensional Discrete Fourier Transform, Two Dimensional Discrete Fourier Transform, Properties of FourierTansform.

Digital Image Transforms

Unitary Transforms, Walsh Transform, Hadamard Transform, The Discrete Cosine Transform, Slant Transform, Optimum transform: Karhunen – Loewe (Hotelling) transform

Image Enhancement in the Frequency Domain

Basis of Filtering in Frequency Domain, Smoothing Frequency Domain Filters, Sharpening Frequency Domain Filters, Laplacian Enhancement in Frequency Domain, Unsharp masking and high-boost filtering, Homomorphic Filtering

Wavelets and Multiresolution Processing

Introduction, Background, Image Pyramids, Sub-band Coding, Multiresolution Expansions, The Haar Transform, Wavelet Transforms in One Dimension, Wavelet Transforms in Two Dimensions.

Image Compression: Fundamentals

Introduction, Background, Fundamentals, Coding Redundancy, Interpixel Redundancy, Psychovisual Redundancy, Fidelity Criteria, Image Compression Models.

Image Compression : Error Free And Lossy Compression

Error-free compression, Variable-length coding, LZW (Lempel-Ziv-Welch) Coding, Bit-Plane coding, Lossless Predictive Coding,

Image Compression Standards

Introduction, Transform Coding (TC), Wavelet Coding, Binary Image Compression Standards, Video Compression Standards

Morphological Image Processing

Introduction, Basics of Set Theory, Dilation and Erosion, Structuring Element, Opening and Closing, Hit or Miss Transformation, Morphological Algorithms.

Image Registration & Segmentation

Introduction, Registration, Segmentation

Image Representation and Description

Introduction, Representation, Boundary Descriptors, Regional Descriptors, Use of Principal Components for Description.

Image Processing Using Matlab

Introduction, MATLAB Development Environment, Quantization, Point Processing, Region Processing, Image Processing.

Practical’s

Geometric Transformations

A) Translation, Rotation Scaling B) bresenham line C) Mid-Point Circle

Image Enhancement

A) Threshold Of An Image B) Contrast Stretching Of An Image C) Brightness Adjustment of an Image D) Gray Level Slicing

Basic Image Transformations

(A) Log Transformation (B) Power Law Transformation (C)Negation Of An Image

MATLAB Program to plot a Histogram

MATLAB Program for plotting a Histogram of given image

Morphological Operations on Image

A) Opening B) Closing C) Morphological Gradient D) Top-hat Transformation

Histogram Equalization on image

MATLAB Program to apply Histogram Equalization on image

Boundary Detection

MATLAB Program for Boundary Detection

Applying DFT on image matrix & Performing the IDFT

Image Enhancement in Frequency Domain

1. IDEAL LPF 2. BUTTERWORTH LPF 3. GAUSSIAN LPF 4. IDEAL HPF 5. BUTTERWORTH HPF 6. GAUSSIAN HPF

Morphological Operation

1) Opening 2)Closing 3) Erosion 4) Dilation 5) Boundary Extraction

Plot the Image details using histogram

1. Jet Colormap Image 2. Background Estimation 3. Flattened Background Removal 4. Image Thresholding 5. Connected Region 6. Size Distribution Graph 7. Statistical Measurement

BIT PLANE SLICING

Region Filling Morphological Operation

Wavelet Analysis

HOMOMORPHIC FILTERING

Homomorphic Filtering

HISTOGRAM STRETCHING

Matlab program for Histogram Stretching

Lossy Image Compression

Matlab program for Lossy Image Compression

Lossless Image Compression , Error Free Compression

Matlab program for Lossless Image Compression & Error Free Compression

Image Enhancement Statistical Filters

(i) Mean and Median Filters (ii) Max-min and Min-max Filters

High Boost Filtering

Matlab program for High Boost Filtering

HUFFMAN Coding

Matlab program for Huffman Coding

Discrete Cosine Transform and Inverse Discrete Cosine Transform

Matlab program for Discrete Cosine Transform and Inverse Discrete Cosine Transform

Image Preprocessing Techniques

(A) Roberts FilterPrewitt Filter (B)Sobel Filter (C)Laplacian Filter (D)Median Filter

BSc Computer Science PRACTICALS University of Mumbai

2D Linear Convolution, Circular Convolution between two 2D matrices

Circular Convolution expressed as linear convolution plus alias

Linear Cross correlation of a 2D matrix, Circular correlation between two signals and Linear auto correlation of a 2D matrix, Linear Cross correlation of a 2D matrix