Image Processing-II (CSE 19101)
IX Sem B.Tech. CSE
(3-0-0)
Attendance: Students having attendance below 75% will not be allowed to appear in End Sem Exam.
Class Timing:
Monday: 02:30 - 03:25 PM
Tuesday: 03:30 - 04:25 PM
Thursday: 01:30 - 02:25 PM
Marks Distribution:
Mid Sem Exam
30
End Sem Exam
60
Class Test
10
Exam Schedule:
Mid Sem Exam
19th Sep 2018
Time: 3-5 PM
End Sem Exam
24th Nov 2018
Time: 2-5 PM
Class Test
12th Sep 2018
Time: 11-12 PM
Course Content:
Introduction: Image Sampling and Quantization; Image Representation; Image Formats; Relationship between Pixels; Pixel Adjacency; Path, Pixels Connectivity; Connected Set; Boundary; Hole; Distance Measurement; Mathematical Operators used in Image Processing; Image Enhancement Techniques in Spatial Domain; Image Enhancement Techniques in Frequency Domain; Linear and Non-linear Filtering; Restoration.
Segmentation: Pixel-based Approach; Multi-level Thresholding; Local Thresholding; Region-based Approach; Point, Line, and Edge detection; Hough Transform.
Image Morphology: Fundamental Operations; Morphological Algorithms; Mathematical Examples.
Image Compression: Error Criterion; Lossless Compression: Run-length Coding, Huffman Coding, Shannon-Fano Coding, Arithmetic Coding, Block Coding, Contour Coding. Lossy Compression: Block Truncation Compression, Vector Quantization Compression.
Image Representation and Description: Freeman Chain Coding; Binary Tree and Quad Tree Coding; Boundary Extraction; Medial Axis Generation & Thinning; Boundary Descriptors; Regional Descriptors; Topological Descriptors; Relational Descriptors.
Multiresolution Analysis and Wavelet: Pyramidal Coding; Subband Coding; Application of Wavelets.
Related Topics: Image Registration; Image Fusion; Texture Analysis; Color Image Processing.
Text and Reference Books:
Digital Image Processing, R. C. Gonzalez and R. E. woods, Pearson Education.
Digital Image Processing and Analysis, B. Chanda and D. Dutta Mazumdar, PHI.
Digital Image Processing, W. K. Pratt, Wiley-Interscience.
Fundamentals of Digital Image Processing, A. K. Jain, Pearson India Education.
Computer Vision, D. A. Forsyth and J. Ponce, Pearson Education.
Pattern Classification and Scene Analysis, R. O. Duda and P. E. Hart, Wiley.
Course Reference Materials:
DIP-Introduction
Image Enhancement in Spatial Domain
Image Enhancement in Frequency Domain
Image Restoration
Image Segmentation-I
Image Segmentation-II
Canny Edge Detector & Hough Transform
Image Morphology
Research Paper - I on Thinning
Research Paper - II on Thinning
Image Compression
Image Representation and Description
Multilevel Analysis