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Stefano Dobbie | 2022 | ISBN: 1682518531 | English | 270 pages | True PDF | 17 MB [/center]
Symbol recognition is one of the significant applications within the area of pattern recognition. Fields like architecture, cartography, electronics, engineering etc. use domain-dependent graphic notations to develop their designs. The automatic interpretation of such documents, requires processes able to recognize the corresponding alphabets of symbols. Because of this wide range of graphic documents, each one with its own characteristic set of symbols, it is not easy to find a precise definition of a symbol. Optical Character Recognition (OCR) has been a topic of interest for many years. Due to this challenging nature, researchers from industry and academic circles have directed their attentions towards Optical Character Recognition. OCR is a complex problem because of the variety of languages, fonts and styles In which text can be written, and the complex rules of languages etc. Hence, techniques from different disciplines of computer science (i.e. image processing, pattern classification and natural language processing etc. are employed to address different challenges.
This book introduces the reader to the problem. It enlightens the reader with the historical perspectives, applications, challenges and techniques of OCR. Various techniques have been used or simply proposed, during the last 10 years, for recognizing symbols in documents. Differences depend on both application field and researcher's cultural background. The book covers the methods most commonly used in the representation, description, and classification phases to the attention of the reader, and we discuss the main recognition strategies. It also reviews a number of techniques that are representative of the various approaches. The recognition of symbols in graphic documents is an Intensive activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. This book entails the most outstanding symbol recognition methods from different points of view. Open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. The book also discusses future perspectives for symbol recognition. New paradigms in the information society technology, such as keyboardless user interfaces for handheld computers, internet search engines based on graphical queries, on-line symbol recognition in graphics tablets and interactive pen displays, etc. also demand for symbol recognition capabilities, but with different requirements than classic applications.
Stefano Dobbie | 2022 | ISBN: 1682518531 | English | 270 pages | True PDF | 17 MB [/center]
Symbol recognition is one of the significant applications within the area of pattern recognition. Fields like architecture, cartography, electronics, engineering etc. use domain-dependent graphic notations to develop their designs. The automatic interpretation of such documents, requires processes able to recognize the corresponding alphabets of symbols. Because of this wide range of graphic documents, each one with its own characteristic set of symbols, it is not easy to find a precise definition of a symbol. Optical Character Recognition (OCR) has been a topic of interest for many years. Due to this challenging nature, researchers from industry and academic circles have directed their attentions towards Optical Character Recognition. OCR is a complex problem because of the variety of languages, fonts and styles In which text can be written, and the complex rules of languages etc. Hence, techniques from different disciplines of computer science (i.e. image processing, pattern classification and natural language processing etc. are employed to address different challenges.
This book introduces the reader to the problem. It enlightens the reader with the historical perspectives, applications, challenges and techniques of OCR. Various techniques have been used or simply proposed, during the last 10 years, for recognizing symbols in documents. Differences depend on both application field and researcher's cultural background. The book covers the methods most commonly used in the representation, description, and classification phases to the attention of the reader, and we discuss the main recognition strategies. It also reviews a number of techniques that are representative of the various approaches. The recognition of symbols in graphic documents is an Intensive activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. This book entails the most outstanding symbol recognition methods from different points of view. Open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. The book also discusses future perspectives for symbol recognition. New paradigms in the information society technology, such as keyboardless user interfaces for handheld computers, internet search engines based on graphical queries, on-line symbol recognition in graphics tablets and interactive pen displays, etc. also demand for symbol recognition capabilities, but with different requirements than classic applications.
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