This book covers up-to-date methods and algorithms for the automated analysis of engineering drawings and digital cartographic maps. The Non-Deterministic Agent System (NDAS) offers a parallel computational approach to such image analysis. The book describes techniques suitable for persistent and explicit knowledge representation for engineering drawings and digital maps. It also highlights more specific techniques, e.g., applying robot navigation and mapping methods to this problem. Also included are more detailed accounts of the use of unsupervised segmentation algorithms to map images. Finally, all these threads are woven together in two related systems: NDAS and AMAM (Automatic Map Analysis Module).
Line drawing interpretation is a challenging area with enormous practical potential. At present, many companies throughout the world invest large amounts of money and human resource in the input of paper drawings into computers. The technology needed to produce an image of a drawing is widely available, but the transformation of these images into more useful forms is an active field of research and development. Machine Interpretation of Line Drawing Images - describes the theory and practice underlying the computer interpretation of line drawing images and - shows how line drawing interpretation systems can be developed. The authors show how many of the problems can be tackled and provide a thorough overview of the processes underpinning the interpretation of images of line drawings.
The image analysis community has put much effort into developing systems for the automatic reading of various types of documents containing text, graphic information, and pictures. A closely related but much more problematic task is the reading and interpretation of line drawings such as maps, engineering drawings, and diagrams. This book considers the problem in detail, analyzes its theoretical foundations, and analyzes existing approaches and systems.
This book constitutes the strictly refereed post-workshop proceedings of the Second International Workshop on Graphics Recognition, GREC'97, held in Nancy, France, in August 1997. The 34 thoroughly revised full papers presented were carefully selected for inclusion in the book on the basis of a second round of post-workshop reviewing. The book is divided into sections on vectorization and segmentation, symbol recognition, form processing, map processing, engineering drawings, applications and systems, performance evaluation, and a graphics recognition contest.
Optical character recognition and document image analysis have become very important areas with a fast growing number of researchers in the field. This comprehensive handbook with contributions by eminent experts, presents both the theoretical and practical aspects at an introductory level wherever possible.
The book focuses on one of the key issues in document image processing – graphical symbol recognition, which is a sub-field of the larger research domain of pattern recognition. It covers several approaches: statistical, structural and syntactic, and discusses their merits and demerits considering the context. Through comprehensive experiments, it also explores whether these approaches can be combined. The book presents research problems, state-of-the-art methods that convey basic steps as well as prominent techniques, evaluation metrics and protocols, and research standpoints/directions that are associated with it. However, it is not limited to straightforward isolated graphics (visual patterns) recognition; it also addresses complex and composite graphical symbols recognition, which is motivated by real-world industrial problems.
This book is the outcome of the successful NATO Advanced Study Institute on Pattern Recognition Theory and Applications, held at St. Anne's College, Oxford, in April 1981., The aim of the meeting was to review the recent advances in the theory of pattern recognition and to assess its current and future practical potential. The theme of the Institute - the decision making aspects of pattern recognition with the emphasis on the novel hybrid approaches - and its scope - a high level tutorial coverage of pattern recognition methodologies counterpointed with contrib uted papers on advanced theoretical topics and applications - are faithfully reflected by the volume. The material is divided into five sections: 1. Methodology 2. Image Understanding and Interpretation 3. Medical Applications 4. Speech Processing and Other Applications 5. Panel Discussions. The first section covers a broad spectrum of pattern recognition methodologies, including geometric, statistical, fuzzy set, syntactic, graph-theoretic and hybrid approaches. Its cove,r age of hybrid methods places the volume in a unique position among existing books on pattern recognition. The second section provides an extensive treatment of the topical problem of image understanding from both the artificial intelligence and pattern recognition points of view. The two application sections demonstrate the usefulness of the novel methodologies in traditional pattern 'recognition application areas. They address the problems of hardware/software implementation and of algorithm robustness, flexibility and general reliability. The final section reports on a panel discussion held during the Institute.
1 Thisbookcontainsrefereedandimprovedpaperspresentedatthe5thIAPR - ternational Workshop on Graphics Recognition (GREC 2003). GREC 2003 was held in the Computer Vision Center, in Barcelona (Spain) during July 30–31, 2003. TheGRECworkshopisthemainactivityoftheIAPR-TC10,theTechnical 2 Committee on Graphics Recognition . Edited volumes from the previous wo- shops in the series are available as Lecture Notes in Computer Science: LNCS Volume 1072 (GREC 1995 at Penn State University, USA), LNCS Volume 1389 (GREC 1997 in Nancy, France), LNCS Volume 1941 (GREC 1999 in Jaipur, India), and LNCS Volume 2390 (GREC 2001 in Kingston, Canada). Graphics recognition is a particular ?eld in the domain of document ana- sis that combines pattern recognition and image processing techniques for the analysis of any kind of graphical information in documents, either from paper or electronic formats. Topics of interest for the graphics recognition community are: vectorization; symbol recognition; analysis of graphic documents with - agrammatic notation like electrical diagrams, architectural plans, engineering drawings, musical scores, maps, etc. ; graphics-based information retrieval; p- formance evaluation in graphics recognition; and systems for graphics recog- tion. Inadditiontotheclassicobjectives,inrecentyearsgraphicsrecognitionhas faced up to new and promising perspectives, some of them in conjunction with other, a?ne scienti?c communities. Examples of that are sketchy interfaces and on-line graphics recognition in the framework of human computer interaction, or query by graphic content for retrieval and browsing in large-format graphic d- uments, digital libraries and Web applications. Thus, the combination of classic challenges with new research interests gives the graphics recognition ?eld an active scienti?c community, with a promising future.
The two volumes CCIS 546 and 547 constitute the refereed proceedings of the CCF Chinese Conference on Computer Vision, CCCV 2015, held in Xi'an, China, in September 2015. The total of 89 revised full papers presented in both volumes were carefully reviewed and selected from 176 submissions. The papers address issues such as computer vision, machine learning, pattern recognition, target recognition, object detection, target tracking, image segmentation, image restoration, face recognition, image classification.
