Image Processing Series
This course Include
1) 47 videos (check curriculum + update will coming before exams)
2) Hand made Notes
3)Strategy to score good marks in Image processing (video will be out before final exams)
- Introduction to Image processing
- Linear Stretching
- Histogram Equalization
- Improved gray-scale (IGS)
- Bit Plane Slicing
- DFT in Image processing
- DIT-FFT in Image Processing
- DIF-FFT in image processing
- Hadamard Transform
- Walsh Transform
- DCT (Discrete Cosine Transform )
- Haar Transform
- Opening and Closing (Morphological Operation )
- Dilation and Erosion (Morphological Operation )
- HIT and MISS (Morphological Operation )
- Hough Transform
- Homomorphic Filtering
- Data Compression (Lossy and Lossless)
- Unitary matrix
- Difference Between Lossy vs Lossless Compression
- Color models (RGB,CMY,HSI )
- Zero Memory Point Operation
- Fidelity Criteria
- Moments with Example
- Thresholding in Image Processing
- Region Growing in Image Segmentation
- Region Splitting in Image Segmentation
- Region Merging in Image Segmentation
- DIT FFT
- Image File Format
- Bitmap Image File Format
- JPEG Image File Format
- Tagged Image File Format (TIFF)
- Gray Level Transformation
- Convolution , Mask and Filtering
- Edge Detection
- Prewitt and Sobel Mask
- Robinson and Kirsch Mask
- Chain Code and Normalize Chain Code
- Huffman and Run Length Encoding (Compression Method Part 1)
- Arithmetic Coding ( Compression method part 2)
- Image Redundancies
- Vector Quantization
- IGS with BPP, MSE and PSNR
- JPEG Compression
- Low pass filter and High Pass Filter in Frequency Domain
- How to pass in Image processing | Importance + Strategy
Image Processing is the semester 5 subject of IT engineering offered by Mumbai Universities. Prerequisite for studying these subject is Mathematics and Statistics.
As images are two dimensional signals, the single dimensional Digital Signal Processing fundamentals. Course Objectives of the subject Image Processing are as follows the course will help the students to get familiar with Fundamental concepts of a digital image processing system. Concepts of image enhancement techniques. Various Image Transforms. Compression techniques and Morphological concepts. Various segmentation techniques, and object descriptors. Color models and various applications of image processing. Course Outcomes of the subject Image Processing are as follows Students should be able to remember the fundamental concepts of image processing. Explain different Image enhancement techniques. Understand and review image transforms. Analyze the basic algorithms used for image processing &image compression with morphological image processing. Contrast Image Segmentation and Representation. Design & Synthesize Color image processing and its real world applications.
Digital image processing is the use of a digital computer to process digital images through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing. It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and distortion during processing. Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems. The generation and development of digital image processing are mainly affected by three factors: first, the development of computers; second, the development of mathematics (especially the creation and improvement of discrete mathematics theory); third, the demand for a wide range of applications in environment, agriculture, military, industry and medical science has increased.
Module Introduction to digital image processing system covers the following subtopics such as Fundamental Steps in Digital Image Processing, Components of an Image Processing System, Image Sensing and Acquisition, Image Sampling and Quantization, Basic Relationships between Pixels.
Module Image enhancement covers the following subtopics such as Intensity Transformations and Spatial Filtering, Histogram processing, Filtering in Frequency Domain.
Module Image transforms covers the following subtopics such as Discrete Fourier transform – Properties of two dimensional DFT, DCT, DST, Walsh, Hadamard, Haar Transform and their properties.
Module Image compression and morphological image processing covers the following subtopics such as Fundamentals of compression, Basic compression Methods, Huffman Coding, Arithmetic Coding , LZW Coding , RunLength Coding , Symbol-Based Coding, Bit-Plane Coding, Block Transform Coding , Predictive Coding. Image morphology, Opening & Closing, Hit or Miss Transform, Basic Morphological Algorithms
Module Image segmentation and representation covers the following subtopics such as The detection of discontinuities – Point, Line and Edge detections , Hough Transform, Thresholding Region based segmentation Chain codes, Polygon approximation, Shape numbers, Fourier descriptors, statistical Moments.
Module Color Image Processing and Applications covers the following subtopics such as Color Fundamentals and Models, Pseudocolor Image Processing, Smoothing and Sharpening, Image Segmentation Based on Color. Biometric Authentication, Digital watermarking, Content Base Image Retrieval. Vector quantization.
Suggested Text Books for these subject Image Processing by Mumbai University are as follows Rafael C. Gonzalez and Richard E.woods, “Digital Image Processing”, Addition – Wesley Publishing Company, New Delhi, Third Edition, 2007. William K. Pratt, “Digital Image Processing”, John Wiley, NJ, Fourth Edition 2007. Suggested Reference Books for these subject Image Processing by Mumbai University are as follows Sid Ahmed M.A., “Image Processing Theory, Algorithm and Architectures”, McGraw-Hill, 1995. Kenneth R Castleman, “Digital Image Processing”, Prentice Hall, New Delhi, 1996. Anil.K.Jain, “Fundamentals of Digital Image Processing”, Prentice Hall of India Pvt Ltd., New Delhi, 1995. S. Sridhar, “ Digital Image Processing”, second Edition, Oxford university press, New Delhi, 2016. S. Jayaraman, S. Esakkirajan, T. Veerakumar “ Digital Image Processing”, McGraw-Hill, 2016.
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- Lectures 48
- Quizzes 0
- Duration 4 hours
- Skill level All levels
- Language Hindi
- Students 107
- Certificate No
- Assessments Yes