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Pattern Recognition Techniques, Technology and Applications
Edited by Peng-Yeng Yin, ISBN 978-953-7619-24-4, Hard cover, 626 pages, Publisher: InTech, Published: November 01, 2008 under CC BY-NC-SA 3.0 license, in subject Artificial Intelligence
A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition.
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Book contents
- Chapter 1Local Energy Variability as a Generic Measure of Bottom-Up Salience
- Chapter 2Real-Time Detection of Infrared Profile Patterns and Features Extraction
- Chapter 3A Survey of Shape Feature Extraction Techniques
- Chapter 4Computational Intelligence Approaches to Brain Signal Pattern Recognition
- Chapter 5Automatic Calibration of Hybrid Dynamic Vision System for High Resolution Object Tracking
- Chapter 6Image Representation Using Fuzzy Morphological Wavelet
- Chapter 7Multidimensional Texture Analysis for Unsupervised Pattern Classification
- Chapter 8Rock Particle Image Segmentation and Systems
- Chapter 9Unsupervised Texture Segmentation
- Chapter 10Optimization of Goal Function Pseudogradient in the Problem of Interframe Geometrical Deformations Estimation
- Chapter 11New Digital Approach to CNN On-chip Implementation for Pattern Recognition
- Chapter 12Distortion-Invariant Pattern Recognition with Adaptive Correlation Filters
- Chapter 13Manifold Matching for High-Dimensional Pattern Recognition
- Chapter 14Output Coding Methods: Review and Experimental Comparison
- Chapter 15Activity Recognition Using Probabilistic Timed Automata
- Chapter 16Load Time-Series Classification Based on Pattern Recognition Methods
- Chapter 17Theory of Cognitive Pattern Recognition
- Chapter 18Parametric Circle Approximation Using Genetic Algorithms
- Chapter 19Registration of Point Patterns Using Modern Evolutionary Algorithms
- Chapter 20Investigation of a New Artificial Immune System Model Applied to Pattern Recognition
- Chapter 21Designing a Pattern Recognition Neural Network with a Reject Output and Many Sets of Weights and Biases
- Chapter 22A SIFT-Based Fingerprint Verification System Using Cellular Neural Networks
- Chapter 23The Fourth Biometric - Vein Recognition
- Chapter 24A Hybrid Pattern Recognition Architecture for Cutting Tool Condition Monitoring
- Chapter 25Mining Digital Music Score Collections: Melody Extraction and Genre Recognition
- Chapter 26Application of Forward Error Correcting Algorithms to Positioning Systems
- Chapter 27Pattern Recognition in Time-Frequency Domain: Selective Regional Correlation and Its Applications
