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13E064SDOS - Image Processing Systems

Course specification
Course title Image Processing Systems
Acronym 13E064SDOS
Study programme Electrical Engineering and Computing
Module
Type of study bachelor academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 6.0 Status mandatory
Condition none
The goal Introducing students to basic system components and concepts of digital picture processing.
The outcome Empowering of the students to use known algorithms for digital image processing and to create and develop new algorithms, as well as computer codes for the processing.
Contents
URL to the subject page http://nobel.etf.bg.edu.rs/studiranje/kursevi/of4sdo/
URL to lectures https://teams.microsoft.com/l/team/19%3au5OckacQX-K-m7CF9Fw-BY0aLZqUyW2hQiOqk9Jmx_g1%40thread.tacv2/conversations?groupId=dbb46298-1920-4f69-ba11-7ed2c56b8923&tenantId=1774ef2e-9c62-478a-8d3a-fd2a495547ba
Contents of lectures Concepts of the digital processing of bidimensional signals. Sensors and aquision of the picture. Discretisaton and digitalization. Basic processing in space domain. Processing in transformational domain. Segmentation and classification of the objects. Picture compression. Archiving, transfer and presentation of the picture.
Contents of exercises Auditory exercises following the lectures. Exercises in a computer lab.
Literature
  1. Rafael Gonzales, Richard Woods, Digital Image Processing, 2nd Ed., Prentice Hall, 2002
  2. Rafael Gonzales, Richard Woods, Steven Eddins, Digital Image Processing using Matlab, Prentice Hall, 2004
  3. C.Solomon, T.Breckon, Fundamentals of Digital Image Processing - A Practical Approach with Examples in Matlab, John Wiley & Sons, 2011.
  4. Jasjit Suri, Kamaledin Setarehdan, Sameer Singh, Eds., Advanced Algorithmic Approaches to Medical Image Segmentation, Springer, 2002
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
3 1 1
Methods of teaching Lectures, auditory and laboratory exercises in a computer lab.
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures 0 Test paper 40
Practical lessons 0 Oral examination 0
Projects
Colloquia 30
Seminars 30