H Bunke

P S P Wang

S Impedovo

The widespread use of bankchecks in daily life makes the development of check-reading systems of fundamental relevance to banks and other financial institutions. This will improve productivity and allow advanced customer services. Therefore, many industrial companies and academic research laboratories have recently been attracted to this field, which involves several aspects, like image acquisition and preprocessing, layout analysis, preprinted data identification and recognition, user-entered data extraction, recognition of handwritten characters and words, and signature verification. The contributions collected in this book present the state of the art in the field of complete systems for bankcheck recognition, and explore the most promising trends in key aspects of this research field. Contents:Automatic Bankcheck Processing: A New Engineered System (G Dimauro et al.)A Prototype for Brazilian Bankcheck Recognition (L L Lee et al.)Automatic Reading of Handwritten Amounts on French Checks (M Leroux et al.)Bankcheck Recognition Using Cross Validation Between Legal and Courtesy Amounts (G Kim & V Govindaraju)An Evolutionary Approach to the Use of Neural Networks in the Segmentation of Handwritten Numerals (J M Westall & M S Narasimha)An Off Line Cursive Handwritten Word Recognition System and Its Application to Legal Amount Interpretation (K Han & I K Sethi)Optimal Order of Markov Models Applied to Bankchecks (C Olivier et al.)A Cognitive Approach to Off-Line Signature Verification (N A Murshed et al.)and other papers Readership: Students and researchers in artificial intelligence and employees of banks and other financial institutions. keywords:

Automatic Bankcheck Processing

A Sanfeliu

This book is currently the only one on this subject containing both introductory material and advanced recent research results. It presents, at one end, fundamental concepts and notations developed in syntactic and structural pattern recognition and at the other, reports on the current state of the art with respect to both methodology and applications. In particular, it includes artificial intelligence related techniques, which are likely to become very important in future pattern recognition. The book consists of individual chapters written by different authors. The chapters are grouped into broader subject areas like “Syntactic Representation and Parsing”, “Structural Representation and Matching”, “Learning”, etc. Each chapter is a self-contained presentation of one particular topic. In order to keep the original flavor of each contribution, no efforts were undertaken to unify the different chapters with respect to notation. Naturally, the self-containedness of the individual chapters results in some redundancy. However, we believe that this handicap is compensated by the fact that each contribution can be read individually without prior study of the preceding chapters. A unification of the spectrum of material covered by the individual chapters is provided by the subject and author index included at the end of the book. Contents:Introduction and Overview (M G Thomason)String Grammars for Syntactic Pattern Recognition (H Bunke)Parsing and Error-Correcting Parsing for String Grammars (E Tanaka)Array, Tree, and Graph Grammars (A Rosenfeld)String Matching for Structural Pattern Recognition (H Bunke)Matching Tree Structures (A Sanfeliu)Matching Relational Structures Using Discrete Relaxation (L G Shapiro & R M Haralick)Random Graphs (A K C Wong et al.)Grammatical Inference (L Miclet)An Algorithm for Inferring Context-Free Array Grammars (P S P Wang & X W Dai)Hybrid Pattern Recognition Methods (H Bunke)Combining Statistical and Structural Methods (W H Tsai)Industrial Applications (H S Baird)Three-Dimensional Object Recognition by Attributed Graphs (E K Wong)Chinese Character Recognition (J W Tai & Y J Liu)Table Driven Parsing for Shape Analysis (T C Henderson & A Samal)A General Purpose Line Drawing Analysis System (R Mohr)ECG Analysis (E Skordalakis) Readership: Graduates, undergraduates, researchers and practising professionals in pattern recognition.

Syntactic and Structural Pattern Recognition — Theory and Applications

H Baird

Interest in the automatic processing and analysis of document images has been rapidly increasing during the past few years. This book addresses the different subfields of document image analysis, including preprocessing and segmentation, form processing, handwriting recognition, line drawing and map processing, and contextual processing. Contents:Preface (H Bunke et al.)A New Parallel Thinning Algorithm (Y Y Zhang & P S P Wang)Background Structure in Document Images (H S Baird)Analysis of Form Images (D Wang & S N Srihari)Model-Based Analysis and Understanding of Check Forms (T M Ha & H Bunke)Document Structures: A Survey (Y Y Tang & C Y Suen)Automatic Input of Logic Diagrams by Recognizing Loop-Symbols and Rectilinear Connections (S H Kim & J H Kim)Syntactic Analysis of Technical Drawing Dimensions (S Collin & D Colnet)Recognition of Elevation Value in Topographic Maps by Multi-Angled Parallelism (H Yamada et al.)Character Recognition by Signature Approximation (N Papamarkos et al.)An Adaptive Modular Neural Network with Application to Unconstrained Character Recognition (L Mui et al.)A Model-Based Split-and-Merge Method for Character String Recognition (H Nishida & S Mori)A Robust Stroke Extraction Method for Handwritten Chinese Characters (H-D Chang & J-F Wang)Handprinted Chinese Character Recognition Using Probability Distribution Feature (T F Li & S S Yu)An Algorithm for Matching OCR-Generated Text Strings (S V Rice et al.) Readership: Computer scientists. keywords:

H Bunke

About

Books

Join the club