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Industrial Management & Data Systems 1992年第2期92卷 17-20页

作者： Perkins, Simon DIP Project Leader at NCC Manchester United Kingdom

There is a reluctance among many companies especially in the UK, toinvest in document image processing (DIP) systems in spite of theresultant cost benefits which have been well documented. Surveys haveshown that the use of DIP has transformed business performance in manyareas and there is no end in sight for the potential applications inthis new technology.

关键词： document image processing Investment Productivity Technological change United Kingdom

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document image processing

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JOURNAL OF IMAGING 2018年第7期4卷 84-84页

作者： Likforman-Sulem, Laurence Kavallieratou, Ergina Univ Paris Saclay Telecom ParisTech Inst Mines Telecom F-75013 Paris France Univ Aegean Dept Informat & Commun Syst Engn Samos 83200 Greece

The Special Issue “document image processing” in the Journal of Imaging aims at presenting approaches which contribute to access the content of document images. These approaches are related to low level tasks such as image preprocessing, skew/slant corrections, binarization and document segmentation, as well as high level tasks such as OCR, handwriting recognition, word spotting or script identification. This special issue brings together 12 papers that discuss such approaches. The first three articles deal with historical document preprocessing. The work by Hanif et al. [1] aims at removing bleed-through using a non-linear model, and at reconstructing the background by an inpainting approach based on non-local patch similarity. The paper by Almeida et al. [2] proposes a new binarization approach that includes a decision-based process for finding the best threshold for each RGB channel. In the paper by Kavallieratou et al. [3], a segmentation-free approach based on the Wigner-Ville distribution is used to detect the slant of a document and correct it.

关键词： document image processing preprocessing document restoration binarization slant removal text-line segmentation handwriting recognition indic/arabic/asian scripts OCR Video OCR word spotting retrieval document datasets performance evaluation document annotation tools

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document image processing for Paper Side Communications

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IEEE TRANSACTIONS ON MULTIMEDIA 2008年第7期10卷 1277-1287页

作者： Borges, Paulo Vinicius Koerich Mayer, Joceli Izquierdo, Ebroul Univ Fed Santa Catarina Dept Elect Engn LPDS BR-88040900 Florianopolis SC Brazil Queen Mary Univ London Dept Elect Engn Multimedia & Vis Lab London E1 4NS England

This paper proposes the use of higher order statistical moments in document image processing to improve the performance of systems which transmit side information through the print and scan channel. Examples of such systems are multilevel 2-D bar codes and certification via text luminance modulation. These systems print symbols with different luminances, according to the target side information. In previous works, the detection of a received symbol is usually performed by evaluating the average luminance or spectral characteristics of the received signal. This paper points out that, whenever halftoning algorithms are used in the printing process, detection can be improved by observing that third and fourth order statistical moments of the transmitted symbol also change, depending on the luminance level. This work provides a thorough analysis for those moments used as detection metrics. A print and scan channel model is exploited to derive the relationship between the modulated luminance level and the higher order moments of a halftone image. This work employs a strategy to merge the different moments into a single metric to achieve a reduced detection error rate. A transmission protocol for printed documents is proposed which takes advantage of the resulting higher robustness achieved with the combined detection metrics. The applicability of the introduced document image analysis approach is validated by comprehensive computer simulations.

关键词： System performance Signs and symbols document image processing higher-order statistical moment Computer Simulation Moment of force Process detection luminance transport protocols halftone image spectral characteristic

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Hierarchical content classification and script determination for automatic document image processing

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PATTERN RECOGNITION 2003年第11期36卷 2483-2500页

作者： Chi, Z Wang, Q Siu, WC Hong Kong Polytech Univ Ctr Multimedia Signal Proc Dept Elect & Informat Engn Hong Kong Hong Kong Peoples R China Northwestern Polytech Univ Dept Comp Sci & Engn Xian 710072 Peoples R China

Page segmentation and image content classification play an important role in automatic image processing with applications to mixed-type document image compression, form and check reading, and automatic mail sorting. In this paper, we first present an enhanced background thinning based approach for fast page segmentation. After the analysis of three different methods individually, a hierarchical approach for document content classification is proposed, which classifies a sub-image into one of two categories: text and halftone. Our approach combines a neural network model, cross-correlation metric, and Kolmogorov complexity measure in a hierarchical structure. Considering the necessity of a recognition system, we also propose using a three-layer feedforward neural network to classify text regions into Chinese and English scripts. The classification accuracy on a number of document images reaches 100% and 97.1% for halftone region and text region, respectively. Meanwhile, the system can achieve a correct rate of 92.3% and 95.0% for Chinese and alphabetic script determination, respectively. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

关键词： document image processing page segmentation content classification script determination background thinning cross-correlation Kolmogorov complexity neural networks

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An application of document image processing to fax communications

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INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY 1997年第1-2期10卷 97-110页

作者： Hui, SC Chan, KY Qian, GY NATL UNIV SINGAPORE INST SYST SCI SINGAPORE 119597 SINGAPORE

This paper focuses on describing how to apply document image processing technology into fax communications. The remainder of this paper is organised as follows. Section 2 introduces the concepts on document image processing. Section 3 describes the fax message analysis process, it focuses on discussing the address block identification and address data analysis. Some experimental results are also given. Section 4 describes the system architecture and user interface of the AutoFax system. Finally, conclusion and future work are given in Section 5.

关键词： document image processing fax communications fax messages address block identification address data analysis

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document image processing based on enhanced border following algorithm

Document image processing based on enhanced border following...

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International Conference on Pattern Recognition

作者： M. Yamada K. Hasuike Research and Development Laboratories Kokusai Denshin Denwa Company Limited Kamifukuoka Saitama Japan

An enhanced border-following algorithm and its application to document image processing is presented. Various kinds of components (characters, text lines, text blocks, figures, tables, etc.) in a document image can be flexibly segmented and extracted with a variable-size mask for border following instead of the conventional 3*3-size mask. An automatic document image structuring process to construct a multimedia document and a raster/geometric conversion method for the segmented graphic parts of the image. such as diagrams and tables, are discussed.< >

关键词： document image processing image segmentation image converters image analysis Graphics Information analysis image processing Pixel Research and development Laboratories

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A Novel Arc Segmentation Approach for document image processing

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2015年第1期29卷 1553001-1553001页

作者： Zhang, Zili Wang, Xuan Han, Kai Jiang, Zoe L. Harbin Inst Technol Shenzhen Grad Sch Comp Applicat Res Ctr Shenzhen Peoples R China Shenzhen Appl Technol Engn Lab Internet Multimedi Shenzhen 518055 Peoples R China

In document image processing, arc segmentation plays an important role in vectorization and graphic recognition. Moreover, the unsatisfactory results of several recent arc segmentation contests indicate that conventional methods are inadequate. This paper proposes a new arc segmentation algorithm called SymCAve (an acronym for Symmetry axis, Circle fitting and Average distribution points). First, we locate several seed points and adopt three strategies to ensure that the seed points are proper;then we calculate the center and radius utilizing the seed points. Second, the coordinates of the center and radius are adjusted by employing symmetry axes. Third, the average distribution points method is used to verify whether the points on the circumference are all black pixels. It is a complete circle if all of the points are black pixels. Otherwise, it is a partial circle if some of the points are black pixels and are continuous. Based on this information, the start and end angles of the partial circle can be determined. Finally, these arcs are verified to ensure that the results are accurate. images and the evaluation tool were obtained from the GREC Workshop's Arc Segmentation contests, to test the systematic performance of the SymCAve algorithm. The experiments demonstrate that the proposed method can provide promising results. However, the algorithm has some drawbacks: it cannot detect a line with width of one pixel, small angles, and any large radius arcs. It is suited for segmenting images with appropriate symmetry axes.

关键词： document image processing arc segmentation seed point symmetry axis average distribution points circle fitting

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A Survey on document image processing Methods Useful for Assistive Technology for the Blind

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INTERNATIONAL JOURNAL OF image AND GRAPHICS 2015年第1期15卷

作者： Keefer, Robert Bourbakis, Nikolaos Pomiet LLC Dayton OH 45449 USA Wright State Univ Dayton OH 45449 USA

This paper offers a review of the state-of-the-art document image processing methods and their classification by identifying new trends for automatic document processing and understanding. document image processing (DIP) is an important problem related with most of the challenges coming from the image processing field and with applications to digital document summarization, readers for the visually impaired etc. Difficulties in the processing of documents can arise from lighting conditions, page curl, page rotation in 3D, and page layout segmentation. document image processing is usually performed in the context of higher-level applications that require an undistorted document image such as optical character recognition and document restoration/preservation. Typically, assumptions are made to constrain the processing problem in the context of a particular application. In this survey, we categorize document image processing methods on the basis of the technique, provide detailed descriptions of representative methods in each category, and examine their pros and cons. It important to notice here that the DIP field is broad, thus we try to provide a top-down/horizontal survey rather a bottom up. At the same time, we target the area of document readers for the blind, and use this application to guide us in a top-down survey of DIP. Moreover, we present a comparative survey based on important aspects of a marketable system that is dependent on document image processing techniques.

关键词： document image processing skew correction page curl correction document image segmentation

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A rule learning method for academic document image processing

A rule learning method for academic document image processin...

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International Conference on document Analysis and Recognition

作者： A. Takasu S. Satoh E. Katsura Res. & Dev. Dept. Nat. Center for Sci. Inf. Syst. Tokyo Japan Research and Development Department National Center for Science Information System Bunkyo Tokyo Japan Facilty of Design Tokyo University of Art and Design Hachioji Tokyo Japan

A syntactic rule learning method is presented for analyzing document images and constructing a database from them. This method is used in a digital library system named CyberMagazine, where document images are sequentially converted into database tuples by block segmentation, rough classification, and syntactic analysis. The syntactic rule has an ability to analyze symbols located in two dimensional plane, and has a syntax similar to an ordinal context free grammar except for the concatenation of symbols. In the presented learning method, the syntactic rules are generated from a set of parse trees by decomposing the trees according to non terminal symbols, generalizing the decomposed trees to a syntactic rule, and merging them.

关键词： Learning systems document image processing image databases image analysis image segmentation Classification tree analysis Decision trees image processing image converters Research and development

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Page segmentation and content classification for automatic document image processing

Page segmentation and content classification for automatic d...

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International Symposium on Intelligent Multimedia, Video and Speech processing

作者： S.K. Yip Z. Chi Center for Multimedia Image Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hung Hom Hong Kong China

ISBN: (纸本)9628576623

Page segmentation and image content classification is an important step for automatic document image processing including mixed-type document image compression, form and check reading, and mail sorting. The authors first propose an enhanced background thinning based page segmentation approach. They then present a hierarchical approach for the classification of the segmented sub-images into one of two categories: text and picture. The approach combines a cross-correlation method, the Kolmogorov complexity measure (A.N. Kolmogorov, 1965), and a neural network classifier in order to achieve both efficiency and high accuracy. Our approach has been tested on a number of mixed-type document images with good results.

关键词： image segmentation document image processing Character recognition Correlation Neural networks Testing image analysis image processing image coding Postal services

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