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19D051OPDOS - Selected Applications of Digital Image Processing

Course specification
Course title Selected Applications of Digital Image Processing
Acronym 19D051OPDOS
Study programme Electrical Engineering and Computing
Module System Control and Signal Processing
Type of study doctoral studies
Lecturer (for classes)
Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
      ESPB 9.0 Status elective
      Condition None
      The goal Studying of modern day methods of digital image processing in time and frequency domains. Understanding of the compression requirements and realizations. Provide students with the ability to use already made software packages as well as to construct their own algorithms for image processing, extraction and specification of image objects.
      The outcome Enabling students to use already made software packages and to generate their own algorithms for image enhancement, extraction of typical objects, object classification, defining the relationships between objects and relative to the scene.
      Contents
      Contents of lectures Image representation. Linear operators and kernels, Image restoration and feature extraction, Mathematical morphology, Image segmentation via snakes, texture description, motion, and color, Shape description, Parametric transforms, Image matching, Pattern recognition in image, Multispectral image analysis, Security applications, Automatic target detection and tracking.
      Contents of exercises Applications of image processing: Document image analysis, Microscopic image analysis, Quality inspection in industry, Motion control, Automatic target tracking
      Literature
      1. S. T. Bow, "Pattern Recognition and Image Processing", Marcel Dekker, 2002 (Original title)
      2. W. E. Snyder, H. Qi, "Machine Vision", Cambridge University Press, 2004 (Original title)
      3. P. M. Mather, "Computer Processing of Remotely Sensed Images", Willey, 2009 (Original title)
      Number of hours per week during the semester/trimester/year
      Lectures Exercises OTC Study and Research Other classes
      8
      Methods of teaching Lectures, exercises on computer, analysis of recommended literature, home-works, and projects.
      Knowledge score (maximum points 100)
      Pre obligations Points Final exam Points
      Activites during lectures Test paper
      Practical lessons Oral examination 30
      Projects
      Colloquia
      Seminars 70