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AU Image Processing and Pattern Recognition Sem VII - Elective
No Units Titles Sub Titles Chapters
1 Unit 1 Introduction Digital Image Processing and Applications-Image Representation and Modeling-Image Enhancement-Image Restoration-Image Analysis - Image Data Compression VIEW CHAPTERS
2 Unit 2 Digital Image Fundamentals Elements of Visual perception-A simple Image Model-Sampling and Quantization-Some Basic Relationship between Pixels VIEW CHAPTERS
3 Unit 3 Image Transforms Two Dimensional Orthogonal and Unitary Transforms-Properties of Unitary Transforms-One Dimensional DFT-Two Dimensional DFT-Cosine Transforms-Sine transforms-Hadamard Transforms-Haar Transforms - Slant transforms VIEW CHAPTERS
4 Unit 4 Image Enhancement Point Operations-Histogram Modeling-Spatial Operations-Transform Operations VIEW CHAPTERS
5 Unit 5 Image Restoration and Compression Image observation models-Inverse and Wiener Filtering-Pixel Coding - Predictive techniques-Transform Coding of Images VIEW CHAPTERS
6 Unit 6 Statistical and Non-Parametric Decision Making Applications of Pattern Recognition-Baye s Theorem-Multiple Features - Conditionality Independent Features-Decision Boundaries-Unequal Costs of Error-Estimation of Error Rates-Kernel and Window Estimator-Nearest Neighborhood Classification Techniques-Adaptive Decision Boundaries - Adaptive Discriminant Functions VIEW CHAPTERS
7 Unit 7 Clustering Introduction-Hierarchical Clustering-Partitional Clustering VIEW CHAPTERS
8 Unit 8 Artificial Neural Networks Introduction-Nets without Hidden Layers-Nets With Hidden Layers-The Back Propagation Algorithms-Hopfield Nets-Classifying Sex From Facial Images VIEW CHAPTERS
 
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