Graphics Recognition. Recent Advances and New Opportunities


Book Description

This book constitutes the thoroughly refereed post-proceedings of the 7th International Workshop on Graphics Recognition, GREC 2007, held in Curitiba, Brazil in September 2007. The 30 revised full papers presented together with a panel discussion report were carefully selected and improved during two rounds of reviewing and revision. The papers are organized in topical sections on technical documents, maps and diagrams understanding; symbol and shape description and recognition; information retrieval, indexing and spotting; sketching interfaces and on-line processing; feature and primitive analysis and segmentation; performance evaluation and ground truthing.




Document Image Analysis


Book Description

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.




Graphics Recognition. Recent Advances and Perspectives


Book Description

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.




Symbol Spotting in Digital Libraries


Book Description

Pattern recognition basically deals with the recognition of patterns, shapes, objects, things in images. Document image analysis was one of the very ?rst applications of pattern recognition and even of computing. But until the 1980s, research in this ?eld was mainly dealing with text-based documents, including OCR (Optical Character Recognition) and page layout analysis. Only a few people were looking at more speci?c documents such as music sheet, bank cheques or forms. The community of graphics recognition became visible in the late 1980s. Their speci?c interest was to recognize high-level objects represented by line drawings and graphics. The speci?c pattern recognition problems they had to deal with was raster-to-graphics conversion (i.e., recognizing graphical primitives in a cluttered pixel image), text-graphics separation, and symbol recognition. The speci?c problem of symbol recognition in graphical documents has received a lot of attention. The symbols to be recognized can be musical notation, electrical symbols, architectural objects, pictograms in maps, etc. At ?rst glance, the symbol recognition problems seems to be very similar to that of character recognition; - ter all, characters are basically a subset of symbols. Therefore, the large know-how in OCR has been extensively used in graphical symbol recognition: starting with segmenting the document to extract the symbols, extracting features from the s- bols, and then recognizing them through classi?cation or matching, with respect to a training/learning set.




Structural Pattern Recognition with Graph Edit Distance


Book Description

This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED). The book also provides a detailed review of a diverse selection of novel methods related to GED, and concludes by suggesting possible avenues for future research. Topics and features: formally introduces the concept of GED, and highlights the basic properties of this graph matching paradigm; describes a reformulation of GED to a quadratic assignment problem; illustrates how the quadratic assignment problem of GED can be reduced to a linear sum assignment problem; reviews strategies for reducing both the overestimation of the true edit distance and the matching time in the approximation framework; examines the improvement demonstrated by the described algorithmic framework with respect to the distance accuracy and the matching time; includes appendices listing the datasets employed for the experimental evaluations discussed in the book.




Graphics Recognition. Recent Advances


Book Description

This edited volume contains refereed and improved versions of select papers 1 that were presented at the third IAPR Workshop on Graphics Recognition (GREC’99), held at Rambagh Palace in Jaipur, India, 26–27, September 1999. The workshop was organized by the TC10 (Technical Committee on Graphics Recognition) of the IAPR. Edited volumes from the previous two workshops in this series are also available as Lecture Notes in Computer Science (volumes 1072 and 1389). Graphics recognition is the study of techniques for computer interpretation of images of line drawings and symbols. This includes methods such as vectori- tion, symbol recognition, and table and chart recognition for applications such as engineering drawings, schematics, logic drawings, maps, diagrams, and musical scores. Some recently developed techniques include graphics-based information or drawing retrieval and recognition of online graphical strokes. With the recent advances in the ?eld, there is now a need to develop benchmarks for evaluating and comparing algorithms and systems. Graphics recognition is a growing ?eld of interest in the broader document image recognition community. The GREC’99 workshop was attended by ?fty-?ve people from ?fteen co- tries. The workshop program consisted of six technical sessions. Each session began with a half-hour invited talk which was followed by several short talks. Each session closed with a half-hour panel discussion where the authors ?elded questions from the other participants. Several interesting new research directions were discussed at the workshop.




Graph Classification And Clustering Based On Vector Space Embedding


Book Description

This book is concerned with a fundamentally novel approach to graph-based pattern recognition based on vector space embedding of graphs. It aims at condensing the high representational power of graphs into a computationally efficient and mathematically convenient feature vector.This volume utilizes the dissimilarity space representation originally proposed by Duin and Pekalska to embed graphs in real vector spaces. Such an embedding gives one access to all algorithms developed in the past for feature vectors, which has been the predominant representation formalism in pattern recognition and related areas for a long time.




Digital Imaging for Cultural Heritage Preservation


Book Description

This edition presents the most prominent topics and applications of digital image processing, analysis, and computer graphics in the field of cultural heritage preservation. The text assumes prior knowledge of digital image processing and computer graphics fundamentals. Each chapter contains a table of contents, illustrations, and figures that elucidate the presented concepts in detail, as well as a chapter summary and a bibliography for further reading. Well-known experts cover a wide range of topics and related applications, including spectral imaging, automated restoration, computational reconstruction, digital reproduction, and 3D models.




Geoinformation from the Past


Book Description

Hendrik Herold explores potentials and hindrances of using retrospective geoinformation for monitoring, communicating, modeling, and eventually understanding the complex and gradually evolving processes of land cover and land use change. Based on a comprehensive review of literature, available data sets, and suggested algorithms, the author proposes approaches for the two major challenges: To address the diversity of geographical entity representations over space and time, image segmentation is considered a global non-linear optimization problem, which is solved by applying a metaheuristic algorithm. To address the uncertainty inherent to both the data source itself as well as its utilization for change detection, a probabilistic model is developed. Experimental results demonstrate the capabilities of the methodology, e.g., for geospatial data science and earth system modeling.




Human-Computer Interaction: Interaction Modalities and Techniques


Book Description

The five-volume set LNCS 8004--8008 constitutes the refereed proceedings of the 15th International Conference on Human-Computer Interaction, HCII 2013, held in Las Vegas, NV, USA in July 2013. The total of 1666 papers and 303 posters presented at the HCII 2013 conferences was carefully reviewed and selected from 5210 submissions. These papers address the latest research and development efforts and highlight the human aspects of design and use of computing systems. The papers accepted for presentation thoroughly cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. This volume contains papers in the thematic area of human-computer interaction, addressing the following major topics: speech, natural language and auditory interfaces; gesture and eye-gaze based Interaction; touch-based interaction; haptic interaction; graphical user interfaces and visualisation.