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Titlebook: Handbook of Document Image Processing and Recognition; David Doermann,Karl Tombre Reference work 2014 Springer-Verlag London 2014 Computer

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楼主: Malnutrition
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https://doi.org/10.1007/978-3-663-05048-3milar character shapes for a machine reading system. This has led to a greater role being played by language models and other post-processing techniques in the development of successful OCR systems for Asian scripts.
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Analysis of the Logical Layout of Documentsng from many different domains. This chapter provides a comprehensive review of the state of the art in the field of automated document understanding, highlights key methods developed for different target applications, and provides practical recommendations for designing a document understanding system for the problem at hand.
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Machine-Printed Character Recognitionreprocessing, page segmentation, feature extraction, character classification, and language modeling that have been developed for modern character recognition systems. Section “Systems and Applications” introduces available machine-printed OCR systems and applications.
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Asian Character Recognitionmilar character shapes for a machine reading system. This has led to a greater role being played by language models and other post-processing techniques in the development of successful OCR systems for Asian scripts.
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Handprinted Character and Word Recognitionstructure, distribution of strokes inside character bounding box, and frequently separated characters. Then it investigates how the reviewed techniques address such characteristics of the handprinted texts.
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https://doi.org/10.1007/978-3-642-81545-41) objects to be analyzed, foreground or background; (2) primitives of analysis, pixels, connected components, maximal empty rectangles, etc.; (3) strategy of analysis, top-down and bottom-up. The details of classified methods are described and compared with one another to know pros and cons of these methods.
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Miroslav Matousek dipl. Ing.,Jörg Schneiderbetween documents and are addressed in this chapter. These tasks are analyzed in this chapter in a unified perspective because they share several technical features and are sometimes adopted in common applications.
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Page Similarity and Classificationbetween documents and are addressed in this chapter. These tasks are analyzed in this chapter in a unified perspective because they share several technical features and are sometimes adopted in common applications.
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