This book constitutes the refereed proceedings of the 6th International Workshop on Structural and Syntactical Pattern Recognition, SSPR '96, held in Leipzig, Germany in August 1996. The 36 revised full papers included together with three invited papers were carefully selected from a total of 52 submissions. The papers are organized in topical sections on grammars and languages; morphology and mathematical approaches to pattern recognition; semantic nets, relational models and graph-based methods; 2D and 3D shape recognition; document image analysis and recognition; and handwritten and printed character recognition.
Pattern recognition is an active area of research with many applications, some of which have reached commercial maturity. Structural and syntactic methods are very powerful. They are based on symbolic data structures together with matching, parsing, and reasoning procedures that are able to infer interpretations of complex input patterns.This book gives an overview of the latest developments and achievements in the field.
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.
The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.
International Conference on Advances in Pattern Recognition (ICAPR 98) at Plymouth represents an important meeting for advanced research in pattern recognition. There is considerable interest in the areas of image processing, medical imaging, speech recognition, document analysis and character recognition, fuzzy data analysis and neural networks. ICAPR 98 is aimed at providing an international platform for invited research in this multi-disciplinary area. It is expected that the conference will grow in future years to include more research contributions that detail state-of the-art research in pattern recognition. ICAPR 98 attracted contributions from different countries of the highest quality. I should like to thank the programme and organising committee for doing an excellent job in organising this conference. The peer reviewed nature of the conference ensured high quality publications in these proceedings. My personal thanks to Mrs. Barbara Davies who served as conference secretary and worked tirelessly in organising the conference. I thank the organising chair for the local arrangements and our should also key-note, plenary and tutorial speakers for their valuable contributions to the conference. I also thank Springer-Verlag for publishing these proceedings that will be a valuable source of research reference for the readers. Finally, I thank all participants who made this conference successful.
The book provides a comprehensive view of pattern recognition concepts and methods, illustrated with real-life applications in several areas. A CD-ROM offered with the book includes datasets and software tools, making it easier to follow in a hands-on fashion, right from the start.
The paper is organized as follows: In section 2, we describe the no- orientation-discontinuity interfering model based on a Gaussian stochastic model in analyzing the properties of the interfering strokes. In section 3, we describe the improved canny edge detector with an ed- orientation constraint to detect the edges and recover the weak ones of the foreground words and characters; In section 4, we illustrate, discuss and evaluate the experimental results of the proposed method, demonstrating that our algorithm significantly improves the segmentation quality; Section 5 concludes this paper. 2. The norm-orientation-discontinuity interfering stroke model Figure 2 shows three typical samples of original image segments from the original documents and their magnitude of the detected edges respectively. The magnitude of the gradient is converted into the gray level value. The darker the edge is, the larger is the gradient magnitude. It is obvious that the topmost strong edges correspond to foreground edges. It should be noted that, while usually, the foreground writing appears darker than the background image, as shown in sample image Figure 2(a), there are cases where the foreground and background have similar intensities as shown in Figure 2(b), or worst still, the background is more prominent than the foreground as in Figure 2(c). So using only the intensity value is not enough to differentiate the foreground from the background. (a) (b) (c) (d) (e) (f)
This book constitutes the refereed proceedings of the 10th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2004 and the 5th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2004, held jointly in Lisbon, Portugal, in August 2004. The 59 revised full papers and 64 revised poster papers presented together with 4 invited papers were carefully reviewed and selected from 219 submissions. The papers are organized in topical sections on graphs; visual recognition and detection; contours, lines, and paths; matching and superposition; transduction and translation; image and video analysis; syntactics, languages, and strings; human shape and action; sequences and graphs; pattern matching and classification; document image analysis; shape analysis; multiple classifier systems; density estimation; clustering; feature selection; classification; and representation.
The nature of handwriting in our society has significantly altered over the ages due to the introduction of new technologies such as computers and the World Wide Web. With increases in the amount of signature verification needs, state of the art internet and paper-based automated recognition methods are necessary. Pattern Recognition Technologies and Applications: Recent Advances provides cutting-edge pattern recognition techniques and applications. Written by world-renowned experts in their field, this easy to understand book is a must have for those seeking explanation in topics such as on- and offline handwriting and speech recognition, signature verification, and gender classification.
Image processing-from basics to advanced applications Learn how to master image processing and compression with this outstanding state-of-the-art reference. From fundamentals to sophisticated applications, Image Processing: Principles and Applications covers multiple topics and provides a fresh perspective on future directions and innovations in the field, including: * Image transformation techniques, including wavelet transformation and developments * Image enhancement and restoration, including noise modeling and filtering * Segmentation schemes, and classification and recognition of objects * Texture and shape analysis techniques * Fuzzy set theoretical approaches in image processing, neural networks, etc. * Content-based image retrieval and image mining * Biomedical image analysis and interpretation, including biometric algorithms such as face recognition and signature verification * Remotely sensed images and their applications * Principles and applications of dynamic scene analysis and moving object detection and tracking * Fundamentals of image compression, including the JPEG standard and the new JPEG2000 standard Additional features include problems and solutions with each chapter to help you apply the theory and techniques, as well as bibliographies for researching specialized topics. With its extensive use of examples and illustrative figures, this is a superior title for students and practitioners in computer science, wireless and multimedia communications, and engineering.
