Recent Advances In Document Recognition And Understanding
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Recent Advances in Document Recognition and Understanding
In the field of document recognition and understanding, whereas scanned paper documents were previously the only recognition target, various new media such as camera-captured documents, videos, and natural scene images have recently started to attract attention because of the growth of the Internet/WWW and the rapid adoption of low-priced digital cameras/videos. The keys to the breakthrough include character detection from complex backgrounds, discrimination of characters from non-characters, modern or ancient unique font recognition, fast retrieval technique from large-scaled scanned documents, multi-lingual OCR, and unconstrained handwriting recognition. This book aims to present recent advances, applications, and new ideas that are relevant to document recognition and understanding, from technical topics such as image processing, feature extraction or classification, to new applications like camera-based recognition or character-based natural scene analysis. The goal of this book is to provide a new trend and a reference source for academic research and for professionals working in the document recognition and understanding field
Graphics Recognition. Recent Advances and Perspectives
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.
Recent Advances in Document Recognition and Understanding
In the field of document recognition and understanding, whereas scanned paper documents were previously the only recognition target, various new media such as camera-captured documents, videos, and natural scene images have recently started to attract attention because of the growth of the Internet/WWW and the rapid adoption of low-priced digital cameras/videos. The keys to the breakthrough include character detection from complex backgrounds, discrimination of characters from non-characters, modern or ancient unique font recognition, fast retrieval technique from large-scaled scanned documents, multi-lingual OCR, and unconstrained handwriting recognition. This book aims to present recent advances, applications, and new ideas that are relevant to document recognition and understanding, from technical topics such as image processing, feature extraction or classification, to new applications like camera-based recognition or character-based natural scene analysis. The goal of this book is to provide a new trend and a reference source for academic research and for professionals working in the document recognition and understanding field.