| October 27th, 2020 02:20 PM | |
| vikash | Sathyabama Institute of Science and Technology B.E. - Electronics and Telecommunication Engineering SECA3009 Digital Image Processing Syllabus Sathyabama Institute of Science and Technology B.E. - Electronics and Telecommunication Engineering SECA3009 Digital Image Processing Syllabus SATHYABAMA INSTITUTE OF SCIENCE AND TECHNOLOGY SCHOOL OF ELECTRICAL AND ELECTRONICS ENGINEERING SECA3009 DIGITAL IMAGE PROCESSING L T P Credits Total Marks 3 0 0 3 100 UNIT 1 INTRODUCTION 9 Hrs. Image Representation, Components of Digital Image Processing Systems, Image Sensing and Acquisition, Elements of Visual Perception, Image formation model, Image Sampling and Quantization, Relationship between pixels. UNIT 2 IMAGE ENHANCEMENT AND RESTORATION 9 Hrs. Enhancement by Point Processing, Histogram Processing, Arithmetic/Logic Operations, Image Averaging, Spatial Filters for Smoothing and Sharpening, Frequency domain filters for Smoothing and Sharpening; Image Degradation & Restoration Model, Noise Models, Inverse Filtering, Geometric Mean Filter. UNIT 3 IMAGE SEGMENTATION AND COMPRESSION 9 Hrs. Detection of Discontinuities, Edge Linking and boundary Detection, Thresholding, Region based Segmentation, Coding Redundancy, Inter pixel Redundancy, Image Compression model, Error Free Compression, Variable Length Coding, and Lossy Compression. UNIT 4 MORPHOLOGICAL AND COLOUR IMAGE PROCESSING 9 Hrs. Dilation and Erosion, Opening and Closing, Basic Morphological Algorithms: Boundary Extraction, Region Filling, Thickening and Thinning; Colour Image Representation, Colour Models, Pseudo Colour Image Processing, Colour Transformations, Smoothing and Sharpening, Segmentation based on Colour. UNIT 5 MEDICAL IMAGE PROCESSING 9 Hrs. Noise Reduction in Nuclear Medicine Imaging, Contrast enhancement of mammograms, Detection of Spinal Canal, Detection of calcifications by multi-tolerance region growing, Shape analysis of calcifications, Analysis of Ligament Healing. Max. 45 Hrs. COURSE OUTCOMES On completion of the course, student will be able to CO1 - Understand the fundamentals of Digital Image Processing. CO2 - Learn the image enhancement techniques in Spatial and Frequency Domain. CO3 - Model the Noises, Restoration and Compression. CO4 - Analyze segmentation and compression techniques. CO5 - Apply various algorithms for Colour Image Processing. CO6 - Apply various algorithms for Medical Image Processing. TEXT / REFERENCE BOOKS 1. Rafael C. Gonzalez, Richard E. Woods, "Digital Image Processing", 4th Edition, Pearson Education, 2017. 2. Milan Sonka, Vaclav Hlavac, Roger Boyle, "Image Processing Analysis and Machine Vision", Cengage Learning, 4th Edition, 2014. 3. B.Chanda, D.Dutta Majumdar, "Digital Image Processing and Applications", Prentice Hall of India, 2011. 4. William K Pratt, "Digital Image Processing", 4th Edition, John Willey, 2007. 5. Rangaraj M. Rangayyan, “Biomedical Image Analysis”, CRC Press LLC, Boca Raton, FL, 2005. 6. Jain A.K., "Fundamentals of Digital Image Processing", Pearson Education, 1989. END SEMESTER EXAMINATION QUESTION PAPER PATTERN Max. Marks: 100 Exam Duration: 3 Hrs. PART A: 10 Questions of 2 marks each - No choice 20 Marks PART B: 2 Questions from each unit of internal choice, each carrying 16 marks 80 Marks |
