本书介绍涉及各个领域应用的人工智能技术——模式识别及其应用的最新发展。内容涵盖模式识别与机器智能、计算机视觉与图像处理、人脸识别与取证、生物特征身份验证等多种基础方式联合的研究。其应用跨越多个领域——从工程、科学研究和实验，到生物医学和诊断应用，再到身份认证和国土安全。此外，在本书收集的世界一流的模式识别、人工智能和生物特征识别技术领域的专家编写的31章内容中也介绍了人类行为的计算机建模和仿真。
本书是计算机与信息科学以及通信与控制专业研究生和相关专业研究人员的必备参考。
Patrick S.P. Wang（王申培） 美国东北大学教授、上海华东师大紫江学者、台湾科技大学客座教授。
关键词：模式识别、人工智能、生物特征识别、信息安全
目录
Part Ⅰ: Pattern Recognition and Machine Intelligence 1 A Review of Applications of Evolutionary Algorithms in Pattern Recognition 1.1 Introduction 1.2 Basic Notions of Evolutionary Algorithms 1.3 A Review of EAs in Pattern Recognition 1.4 Future Research Directions 1.5 Conclusions References 2 Pattern Discovery and Recognition in Sequences 2.1 Introduction 2.2 Sequence Patterns and Pattern Discovery-A Brief Review. 2.3 Our Pattern Discovery Framework 2.4 Conclusion References 3 A Hybrid Method of Tone Assessment for Mandarin CALL System 3.1 Introduction 3.2 Related Work 3.3 Proposed Approach 3.4 Experimental Procedure and Analysis 3.5 Conclusions References 4 Fusion with Infrared Images for an Improved Performance and Perception 4.1 Introduction 4.2 The Principle of Infrared Imaging 4.3 Fusion with Infrared Images 4.4 Applications 4.5 Summary References 5 Feature Selection and Ranking for Pattern Classification in Wireless Sensor Networks 5.1 Introduction 5.2 General Approach 5.3 Sensor Ranking 5.4 Experiments 5.5 Summary, Discussion and Conclusions References 6 Principles and Applications of RIDED-2D-A Robust Edge Detection Method in Range Images 6.1 Introduction 6.2 Definitions and Analysis 6.3 Principles of Instantaneous Denoising and Edge Detection 6.4 Experiments and Evaluations 6.5 Discussions and Applications 6.6 Conclusions and Prospects References Part Ⅱ: Computer Vision and Image Processing 7 Lens Shading Correction for Dirt Detection 7.1 Introduction 7.2 Background 7.3 Our Proposed Method 7.4 Experimental Results 7.5 Conclusions References 8 Using Prototype-Based Classification for Automatic Knowledge Acquisition 8.1 Introduction 8.2 Prototype-Based Classification 8.3 Methodology 8.4 Application 8.5 Results 8.6 Conclusion References 9 Tracking Deformable Objects with Evolving Templates forReal-Time Machine Vision 9.1 Introduction 9.2 Problem Formulation 9.3 Search Framework for Computing Template Position 9.4 Updating Framework for Computing Template Changes …… Part Ⅲ：Face Recognition and Forensics Part Ⅳ：Biometric Authentication
