Applied Image Processing detailed syllabus for Robotics & Automation Engineering (Robotics) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the Robotics 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.
For Robotics & Automation Engineering 5th Sem scheme and its subjects, do visit Robotics 5th Sem 2021 regulation scheme. For Professional Elective-IV scheme and its subjects refer to Robotics Professional Elective-IV syllabus scheme. The detailed syllabus of applied image processing is as follows.
Course Objectives:
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Unit I
IMAGE FORMATION AND PROCESSING 9
Introduction – Geometric primitives and Transformations – Photometric Image formation – The digital camera. Introduction to image processing – point – spatial – Fourier Transform – Pyramids and wavelets – Geometric transformations – global optimization
Unit II
FEATURE DETECTION AND MATCHING 9
Introduction – Points and patches – Feature detectors – Feature Descriptors – SIFT – PCA SIFT -Gradient location orientation histogram
Unit III
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Unit IV
COMPUTATIONAL PHOTOGRAPHY 9
Photometric calibration – Radiometric response function – Noise level estimation – Vignetting – Optical blur – High dynamic range imaging – Super resolution and blur removal – Color image demos icing -application
Unit V
IMAGE RECOGNITION 9
Object detection – Face recognition – Instance recognition – category recognition – Bag of words -Part based models – context and scene understanding- Application: Image search.
Course Outcomes:
Upon successful completion of the course, students should be able to:
- Understand various image processing and preprocessing techniques.
- Design a feature detection algorithm for given application
- Design a segmentation algorithm for given application.
- Understand and recognize various computational photography techniques.
- Design an image recognition for given application.
Text Books:
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Reference Books:
- Forsyth D A, Ponce J, “Computer Vision: A Modern Approach”, 2nd Edition Bostan Pearson, 2015
- Duda R O, Hart P E, Stork D G, “Pattern Classification”, Wiley, 2001.
- Richard Sc “Computer Vision: Algorithms and Applications”, Springer, 2010.
- Simon J.D.Prince “Computer Vision: Models,Learning and Inference”, Cambridge University Press, New York, 2014.
For detailed syllabus of all the other subjects of Robotics & Automation Engineering 5th Sem, visit Robotics 5th Sem subject syllabuses for 2021 regulation.
For all Robotics & Automation Engineering results, visit Anna University Robotics all semester results direct link.