Computer–Aided Intelligent Recognition Techniques and Applications

Intelligent recognition methods have recently proven to be indispensable in a variety of modern industries, including computer vision, robotics, medical imaging, visualization and the media. Furthermore, they play a critical role in the traditional fields such as character recognition, natural language processing and personal identification.
This cutting–edge book draws together the latest findings of industry experts and researchers from around the globe. It is a timely guide for all those require comprehensive, state–of–the–art advice on the present status and future potential of intelligent recognition technology.
Computer–Aided Intelligent Recognition Techniques and Applications:Provides the user community with systems and tools for application in a very wide range of areas, including: IT, education, security, banking, police, postal services, manufacturing, mining, medicine, multimedia, entertainment, communications, data visualization, knowledge extraction, pattern classification and virtual reality.Disseminates information in a plethora of disciplines, for example pattern recognition, AI, image processing, computer vision and graphics, neural networks, cryptography, fuzzy logic, databases, evolutionary algorithms, shape and numerical analysis.Illustrates all theory with real–world examples and case studies.
This valuable resource is essential reading for computer scientists, engineers, and consultants requiring up–to–date comprehensive guidance on the latest developments in computer–aided intelligent recognition techniques and applications. Its detailed, practical approach will be of interest to senior undergraduate and graduate students as well as researchers and industry experts in the field of intelligent recognition

Spis treści:
Preface.
List of Contributors.
1. On Offline Arabic Character Recognition (Muhammad Sarfraz, Abdulmale k Zidouri, and Syed Nazim Nawaz (Saudi Arabia).
2. License Plate Recognition System: Saudi Arabian Case (Muhammad Sarfraz and Mohammed Jameel Ahmed (Saudi Arabia).
3. Algorithms for Extracting Textual Characters in Color Video (Edward K. Wong and  Minya Chen(USA).
4. Separation of Handwritten Touching Digits: A Multi–Agents Approach (Ashraf Elnagar (UAE ) and Reda Al–Hajj (Canada).
5. Prototype–based Handwriting Recognition using Shape and Execution Prototypes (Miguel L. Bote–Lorenzo, Eduardo Gómez–Sánchez, Yannis A. Dimitriadis (Spain).
6. Logo Detection in Document Images with Complex Backgrounds (Tuan D. Pham and Jinsong Yang (Australia).
7. An Intelligent On–line Signature Verification System (Bin Li (China) and David Zhang (Hong Kong).
8. Hybrid Fingerprint Recognition using Minutiae and Shape (Asker Bazen, Raymond Veldhuis, and Sabih Gerez (The Netherlands).
9. Personal Authentication Using the Fusion of Multiple Palm–print Features (Chin–Chuan Han ( Taiwan, R.O.C.).
10. Intelligent Iris Recognition Using Neural Networks (Muhammad Sarfraz, Mohamed Deriche, Muhammad Moinuddin, and Syed Saad Azhar Ali (Saudi Arabia).
11. Pose Invariant Face Recognition using Subspaces Techniques (Mohamed Deriche and Mohammed Aleemuddin (Saudi Arabia).
12. Developmental Vision: Adaptive Recognition of Human Faces by Humanoid Robots (Hon–fai Chia and Ming Xie (Singapore).
13. Empirical Study on Appearance–based Binary Age Classification (Mohammed Yeasin, Rahul Khare, and Rajeev Sharma (USA).
14. Intelligent Recognition in Medical Pattern Understanding and Cognitive Analysis (Marek R. Ogiela and Ryszard Tadeusiewicz (Poland).
15. T he Road Map for Recognizing Regions of Interest in Medical Images (Sabah M.A. Mohammed, Jinan A.W. Fiaidhi, and Lei Yang (Canada).
16. Feature Extraction and Compression with Discriminative and Nonlinear Classifiers and Applications in Speech Recognition (Xuechuan Wang (Canada).
17. Improving Mine Recognition through Processing and Dempster–Shafer Fusion of Multisensor Data (Nada Milisavljević (Belgium) and Isabelle Bloch (France).
18. Fast Object Recognition Using Dynamic Programming from Combination of Salient Line Groups (Dong Joong Kang, Jong Eun Ha, and In So Kweon (Korea).
19. Holo–Extraction and Intelligent Recognition of Digital Curves Scanned from Paper Drawings (Ke–Zhang Chen, Xi–Wen Zhang, Zong–Ying Ou, and Xin–An Feng(China).
20.  Topological Segmentation and Smoothing of Discrete Curve Skeletons (Wenjie Xie, Renato Perucchio, David Sedmera, and Robert P. Thompson (USA).
21. Applications of Clifford Valued Neural Networks to Pattern Classification and Pose Estimation (Eduardo Bayro–Corrochano and Nancy Arana–Daniel (México).
22. Intelligent Recognition: Components of the Short Time Fourier Transform vs. Conventional Approaches(Leonid Gelman, Mike Sanderson, Chris Thompson, and Paul Anuzis (UK).
23. Conceptual Data Classification: Application for Knowledge Extraction(Ahmed Hasnah, Ali Jaoua, and Jihad Jaam (Qatar).
24.  Cryptographic Communications With Chaotic Semiconductor Lasers (Andrés Iglesias (Spain).
Index.


Nota biograficzna:
Dr. Sarfraz received his B.S.c.in mathematics and statistics from Govt. College, Lahore, Pakistan in 1977, an M.S.c in mathematics and an M.S.c in Numerical Analysis from the University of Brunel. He then went o n to complete his P.h.D in Computer Aided Geometric Design also at The University of Brunel.
Dr. Sarfraz is currently Associate Professor at King Fahd University of Petroleum and Minerals, Saudi Arabia. He is a member of many professional bodies including the IEEE and the IEEE Computer Society. He has published three books and written numerous journal papers and reports.

Okładka tylna:
Intelligent recognition methods have recently proven to be indispensable in a variety of modern industries, including computer vision, robotics, medical imaging, visualization and the media. Furthermore, they play a critical role in the traditional fields such as character recognition, natural language processing and personal identification.
This cutting–edge book draws together the latest findings of industry experts and researchers from around the globe. It is a timely guide for all those require comprehensive, state–of–the–art advice on the present status and future potential of intelligent recognition technology.
Computer–Aided Intelligent Recognition Techniques and Applications:Provides the user community with systems and tools for application in a very wide range of areas, including: IT, education, security, banking, police, postal services, manufacturing, mining, medicine, multimedia, entertainment, communications, data visualization, knowledge extraction, pattern classification and virtual reality.Disseminates information in a plethora of disciplines, for example pattern recognition, AI, image processing, computer vision and graphics, neural networks, cryptography, fuzzy logic, databases, evolutionary algorithms, shape and numerical analysis.Illustrates all theory with real–world examples and case studies.
This valuable resource is essential reading for computer scientists, engineers, and consultants requiring up–to–date comprehensive guidance on the latest developmen