Computational Intelligence in Image Processing Front Cover

Computational Intelligence in Image Processing

  • Length: 320 pages
  • Edition: 2013
  • Publisher:
  • Publication Date: 2012-08-10
  • ISBN-10: 3642306209
  • ISBN-13: 9783642306204
  • Sales Rank: #9709384 (See Top 100 Books)
Description

Computational intelligence based techniques have firmly established themselves as viable, alternate, mathematical tools for more than a decade. They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consumer electronics, robotics, finance, manufacturing systems, electric power systems, and power electronics. Image processing is also an extremely potent area which has attracted the atten­tion of many researchers who are interested in the development of new computational intelligence-based techniques and their suitable applications, in both research prob­lems and in real-world problems.

Part I of the book discusses several image preprocessing algorithms; Part II broadly covers image compression algorithms; Part III demonstrates how computational intelligence-based techniques can be effectively utilized for image analysis purposes; and Part IV shows how pattern recognition, classification and clustering-based techniques can be developed for the purpose of image inferencing. The book offers a unified view of the modern computational intelligence tech­niques required to solve real-world problems and it is suitable as a reference for engineers, researchers and graduate students.

Table of Contents

Part I Image Preprocessing Algorithms
Chapter 1 Improved Digital Image Enhancement Filters Based on Type-2 Neuro-Fuzzy Techniques
Chapter 2 Locally-Equalized Image Contrast Enhancement Using PSO-Tuned Sectorized Equalization
Chapter 3 Hybrid BBO-DE Algorithms for Fuzzy Entropy-Based Thresholding
Chapter 4 A Genetic Programming Approach for Image Segmentation

Part II Image Compression Algorithms
Chapter 5 Fuzzy Clustering-Based Vector Quantization for Image Compression
Chapter 6 Layers Image Compression and Reconstruction by Fuzzy Transforms
Chapter 7 Modified Bacterial Foraging Optimization Technique for Vector Quantization-Based Image Compression

Part III Image Analysis Algorithms
Chapter 8 A Fuzzy Condition-Sensitive Hierarchical Algorithm for Approximate Template Matching in Dynamic Image Sequence
Chapter 9 Digital Watermarking Strings with Images Compressed by Fuzzy Relation Equations
Chapter 10 Study on Human Brain Registration Process Using Mutual Information and Evolutionary Algorithms
Chapter 11 Use of Stochastic Optimization Algorithms in Image Retrieval Problems.
Chapter 12 A Cluster-Based Boosting Strategy for Red Eye Removal

Part IV Image Inferencing Algorithms
Chapter 13 Classifying Pathological Prostate Images by Fractal Analysis
Chapter 14 Multiobjective PSO for Hyperspectral Image Clustering
Chapter 15 A Computational Intelligence Approach to Emotion Recognition from the Lip-Contour of a Subject

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