Pattern Recognition, Machine Intelligence and Biometrics

"Pattern Recognition, Machine Intelligence and Biometrics" covers the most recent developments in Pattern Recognition and its applications, using artificial intelligence technologies within an increasingly critical field. It covers topics such as: image analysis and fingerprint recognition; facial expressions and emotions; handwriting and signatures; iris recognition; hand-palm gestures; and multimodal based research. The applications span many fields, from engineering, scientific studies and experiments, to biomedical and diagnostic applications, to personal identification and homeland security. In addition, computer modeling and simulations of human behaviors are addressed in this collection of 31 chapters by top-ranked professionals from all over the world in the field of PR/AI/Biometrics. The book is intended for researchers and graduate students in Computer and Information Science, and in Communication and Control Engineering. Dr. Patrick S. P. Wang is a Professor Emeritus at the College of Computer and Information Science, Northeastern University, USA, Zijiang Chair of ECNU, Shanghai, and NSC Visiting Chair Professor of NTUST, Taipei. Front Matter....Pages i-xxxix Front Matter....Pages 1-1 A Review of Applications of Evolutionary Algorithms in Pattern Recognition....Pages 3-28 Pattern Discovery and Recognition in Sequences....Pages 29-59 A Hybrid Method of Tone Assessment for Mandarin CALL System....Pages 61-80 Fusion with Infrared Images for an Improved Performance and Perception....Pages 81-108 Feature Selection and Ranking for Pattern Classification in Wireless Sensor Networks....Pages 109-137 Principles and Applications of RIDED-2D —A Robust Edge Detection Method in Range Images....Pages 139-167 Front Matter....Pages 169-169 Lens Shading Correction for Dirt Detection....Pages 171-195 Using Prototype-Based Classification for Automatic Knowledge Acquisition....Pages 197-212 Tracking Deformable Objects with Evolving Templates for Real-Time Machine Vision....Pages 213-235 Human Extremity Detection for Action Recognition....Pages 237-260 Ensemble Learning for Object Recognition and Tracking....Pages 261-278 Depth Image Based Rendering....Pages 279-310 Front Matter....Pages 311-311 Gender and Race Identification by Man and Machine....Pages 313-333 Common Vector Based Face Recognition Algorithm....Pages 335-360 A Look at Eye Detection for Unconstrained Environments....Pages 361-387 Kernel Methods for Facial Image Preprocessing....Pages 389-409 Fingerprint Identification — Ideas, Influences, and Trends of New Age....Pages 411-446 Subspaces Versus Submanifolds — A Comparative Study of Face Recognition....Pages 447-484 Linear and Nonlinear Feature Extraction Approaches for Face Recognition....Pages 485-514 Facial Occlusion Reconstruction Using Direct Combined Model....Pages 515-532 Front Matter....Pages 311-311 Generative Models and Probability Evaluation for Forensic Evidence....Pages 533-559 Feature Mining and Pattern Recognition in Multimedia Forensics—Detection of JPEG Image Based Steganography, Double-Compression, Interpolation and WAV Audio Based Steganography....Pages 561-604 Front Matter....Pages 605-605 Biometric Authentication....Pages 607-631 Radical-Based Hybrid Statistical-Structural Approach for Online Handwritten Chinese Character Recognition....Pages 633-655 Current Trends in Multimodal Biometric System—Rank Level Fusion....Pages 657-673 Off-line Signature Verification by Matching with a 3D Reference Knowledge Image — From Research to Actual Application....Pages 675-708 Unified Entropy Theory and Maximum Discrimination on Pattern Recognition....Pages 709-732 Fundamentals of Biometrics —Hand Written Signature and Iris....Pages 733-783 Recent Trends in Iris Recognition....Pages 785-796 Using Multisets of Features and Interactive Feature Selection to Get Best Qualitative Performance for Automatic Signature Verification....Pages 797-821 Fourier Transform in Numeral Recognition and Signature Verification....Pages 823-857 Back Matter....Pages 859-866 'Pattern Recognition, Machine Intelligence and Biometrics' covers the most recent developments in Pattern Recognition and its applications, using artificial intelligence technologies within an increasingly critical field. It covers topics such as: image analysis and fingerprint recognition; facial expressions and emotions; handwriting and signatures; iris recognition; hand-palm gestures; and multimodal based research. The applications span many fields, from engineering, scientific studies and experiments, to biomedical and diagnostic applications, to personal identification and homeland security. In addition, computer modeling and simulations of human behaviors are addressed in this collection of 31 chapters by top-ranked professionals from all over the world in the field of PR/AI/Biometrics. The book is intended for researchers and graduate students in Computer and Information Science, and in Communication and Control Engineering. Dr. Patrick S.P. Wang is a Professor Emeritus at the College of Computer and Information Science, Northeastern University, USA, Zijiang Chair of ECNU, Shanghai, and NSC Visiting Chair Professor of NTUST, Taipei