{"id":54957,"date":"2023-08-27T04:02:12","date_gmt":"2023-08-27T04:02:12","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/cei347-digital-image-processing-syllabus-for-eie-2021-regulation-professional-elective-v\/"},"modified":"2023-08-27T04:02:12","modified_gmt":"2023-08-27T04:02:12","slug":"cei347-digital-image-processing-syllabus-for-eie-2021-regulation-professional-elective-v","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/cei347-digital-image-processing-syllabus-for-eie-2021-regulation-professional-elective-v\/","title":{"rendered":"CEI347: Digital Image processing syllabus for EIE 2021 regulation (Professional Elective-V)"},"content":{"rendered":"

Digital Image processing detailed syllabus for Electronics & Instrumentation Engineering (EIE) for 2021 regulation curriculum has been taken from the Anna Universities<\/a> official website and presented for the EIE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below. <\/p>\n

For Electronics & Instrumentation Engineering 6th Sem scheme and its subjects, do visit EIE 6th Sem 2021 regulation scheme<\/a>. For Professional Elective-V scheme and its subjects refer to EIE Professional Elective-V syllabus scheme<\/a>. The detailed syllabus of digital image processing is as follows. <\/p>\n

Course Objectives:<\/h4>\n

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Unit I<\/h4>\n

FUNDAMENTALS OF IMAGE PROCESSING
\nImage perception, MTF of the visual system, Image fidelity criteria, Image model, Image sampling and quantization – two dimensional sampling theory, Image quantization, Optimum mean square quantizer, Image transforms – 2D-DFT and other transforms.\n<\/p>\n

Unit II<\/h4>\n

BIO-MEDICAL IMAGE PREPROCESSING
\nImage Enhancement operations – Image noise and modeling, Image restoration – Image degradation model, Inverse and Wiener filtering, Geometric transformations and correction.\n<\/p>\n

Unit III<\/h4>\n

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Unit IV<\/h4>\n

IMAGE ANALYSIS AND CLASSIFICATION
\nImage segmentation- pixel based, edge based, region based segmentation. Active contour models and Level sets for medical image segmentation, Image representation and analysis, Feature Extraction and Representation-Statistical, Shape, Texture features. Statistical and Neural Network based image classification.\n<\/p>\n

Unit V<\/h4>\n

IMAGE REGISTRATIONS AND VISUALIZATION
\nImage Registration: Rigid body transformation – Affine transformation, Principal axes registration, Iterative principal axes registration, Feature based registration, Elastic deformation based registration, Registration of Images from Different modalities, Evaluation of Registration Methods. Image visualization: 2-D display methods, 3-D display methods, surface and volume based 3-D display methods – Surface Visualization and Volume visualization, 3-D Echocardiography, 3D+time Echocardiography, virtual reality based interactive visualization.<\/p>\n

Skill Development Activities<\/h4>\n

(Group Seminar\/MiniProject\/Assignment\/Content Preparation \/ Quiz\/ Surprise Test \/ Solving GATEquestions\/ etc)<\/p>\n

    \n
  1. Survey different algorithms for segmentation of various medical images.<\/li>\n
  2. Identify suitable open source software for 2D and 3D visualization of medical images.<\/li>\n
  3. Compare various segmentation techniques and its suitability for the given medical image.<\/li>\n
  4. Conduct a literature survey and find the best preprocessing technique for medical images.<\/li>\n
  5. Develop the best Machine learning algorithm to preprocess and classify different images.<\/li>\n<\/ol>\n

    Text Books:<\/h4>\n

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    Reference Books:<\/h4>\n
      \n
    1. Anil K Jain, Fundamentals of Digital Image Processing, 1st Edition, Pearson Education India, 2015.<\/li>\n
    2. Geoff Dougherty, Digital Image Processing for Medical Applications, 1st Edition, Cambridge University Press, 2010.<\/li>\n
    3. Jerry L.Prince and Jonathan M.Links, Medical Imaging Signals and Systems, 2ndEdition, Pearson Education, 2014.<\/li>\n
    4. Kavyan Najarian and Robert Splerstor, Biomedical signals and Image processing, 2ndEdition, CRC Press, 2012.<\/li>\n
    5. Ravikanth Malladi, Geometric Methods in Bio-Medical Image Processing (Mathematics and Visualization), 1st Edition, Springer-Verlag Berlin Heidelberg 2002.<\/li>\n
    6. A. Ardeshir Goshtasby, Image Registration Principles, Tools and Methods (Advances in Computer Vision and Pattern Recognition), Springer 2014.<\/li>\n
    7. Joseph V. Hajnal, Derek L.G. Hill and David J. Hawkes, Medical Image Registration, CRC Press, 2001.<\/li>\n<\/ol>\n

      List of Open Source Software\/ Learning Website:<\/h4>\n