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INDUSTRIAL MANAGEMENT & DATA SYSTEMS 1994年第1期94卷 3-8页

作者： PARKIN, RM DALAY, BS DE MONTFORT UNIV LEICESTERENGLAND

The impact of advances in information technology has been widespread, but the fundamentals of effective communication have remained unchanged. Improvements to documentation tools, such as computer platforms, word processing software and printer output devices, have enabled standards of experiment reporting to be raised. To cultivate further the quality presentation of scientific instrument waveform images, techniques of direct computer interface are presented. Taking advantage of the widespread support of the plotter communications language HPGL, a generalized method for image transfer and incorporation within document processors is developed and supported by examples. The possibility of image enhancement is explored in a computer program that also integrates the supervised transfer of instrument data. The technique has been successfully introduced into several undergraduate student-centred work packages. Among the many benefits have been the significant improvements in the presentation of dissertations.

关键词： COMMUNICATIONS COMPUTERS document image processing

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Learning one-to-many stylised Chinese character transformation and generation by generative adversarial networks

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IET image processing 2019年第14期13卷 2680-2686页

作者： Chen, Jiefu Ji, Yanli Chen, Hua Xu, Xing Univ Elect Sci & Technol China Ctr Future Media Chengdu Sichuan Peoples R China Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu Sichuan Peoples R China Jiangxi Normal Univ Sch Comp & Informat Engn Nanchang Jiangxi Peoples R China

Owing to the complex structure of Chinese characters and the huge number of Chinese characters, it is very challenging and time consuming for artists to design a new font of Chinese characters. Therefore, the generation of Chinese characters and the transformation of font styles have become research hotspots. At present, most of the models on Chinese character transformation cannot generate multiple fonts, and they are not doing well in faking fonts. In this article, the authors propose a novel method of Chinese character fonts transformation and generation based on generative adversarial networks. The authors' model is able to generate multiple fonts at once through font style-specifying mechanism and it can generate a new font at the same time if the authors combine the characteristics of existing fonts.

关键词： character sets optical character recognition document image processing learning (artificial intelligence) feature extraction natural language processing stylised Chinese character transformation generative adversarial networks Chinese character fonts transformation font style-specifying mechanism

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A robust system for document layout analysis using multilevel homogeneity structure

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EXPERT SYSTEMS WITH APPLICATIONS 2017年 85卷 99-113页

作者： Tuan Anh Tran Oh, Kanghan Na, In-Seop Lee, Guee-Sang Yang, Hyung-Jeong Kim, Soo-Hyung HoChiMinh City Univ Technol Fac Comp Sci & Engn 268 Ly Thuong KietDist 10 Ho Chi Minh City Vietnam Chonnam Natl Univ Sch Elect & Comp Engn 77 Yongbong Ro Gwangju 500757 South Korea

One of the difficulties in the understanding of document images is document layout analysis, which is the first step in document image modeling. In this paper, a robust system for which a multilevel-homogeneity structure is used in accordance with a hybrid methodology is proposed to deal with this problem. Our system consists of the following three main stages: classification, segmentation, and refinement and labeling. Different from other page segmentation methods, the proposed system includes an efficient algorithm to detect table regions in document images. Besides, to create an effective application, the proposed system is designed to work with a variety of document languages. The proposed method was tested with the ICDAR2015 competition (RDCL-2015) and three other published datasets in different languages. The results of these tests show that the accuracy of proposed system is superior to the previous methods. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： document layout analysis Multilevel homogeneity structure (MHS) Page segmentation document image processing OCR

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A method of post-processing for character recognition based on syntactic and semantic analysis of sentences

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SYSTEMS AND COMPUTERS IN JAPAN 1996年第9期27卷 94-107页

作者： Kise, K Shiraishi, T Takamatsu, S Fukunaga, K College of Engineering University of Osaka Prefecture Sakai Japan 593 Currently with Mitsubishi Electric Corp. Shinobu Takamastu:graduated in 1971 from the Dept. Electrical Eng. Coll. Eng. Univ. of Osaka Pref. where he received his Master's degree in 1973 and his Dr. of Eng. degree later. At present Assoc. Prof. Dept. Computer and Systems Sciences or C.S.S. Univ. of Osaka Pref. He is engaged in research on natural language understanding knowledge information processing and specification description language. He is a member Inf. Proc. Soc. and Soc. Artif. Intel. Member

Post-processing of character recognition refers to the processing used to correct the errors in character recognition. When the input is a string representing a sentence in the highly precise error correction, it is desired that the syntactic as well as semantic examinations should be made at the sentence level. This paper assumes that the morphemes, syntax and semantics of the input sentence can be analyzed, and proposes a method that uses the syntactic and semantic analysis in the post-processing. The proposed method receives the list of candidate characters up to the fifth, and outputs the sentence that is adequate from the viewpoints of both syntax and semantics. The method features the following three points: (1) in word matching, it is examined also whether or not a sentence adequate from the viewpoints of syntax and semantics can he composed, and then the inadequate words extraction is inhibited;(2) characters having stronger syntactic and semantic constraints, such as the single-character particle and the conjugational suffix, are estimated top-down. Then, the case where the adequate character is not contained in the candidates can be handled;and (3) the words for which the adequateness cannot be determined from the syntactic or semantic viewpoint are selected by character re-recognition processing. An experiment is executed for 50 sample sentences. The character recognition rate is improved from 83.0 percent to 98.0 percent, and the sentence recognition rate is improved from 10.0 percent to 94.0 percent. Compared to the method based only on word matching, the sentence recognition rate is improved by more than 20 percent. In other words, the effectiveness of the proposed method is demonstrated.

关键词： character recognition postprocessing document image processing document image recognition natural language processing

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A robust and fast skew detection algorithm for generic documents

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PATTERN RECOGNITION 1996年第10期29卷 1599-1629页

作者： Yu, B Jain, AK MICHIGAN STATE UNIV DEPT COMP SCI E LANSING MI 48824 USA

A robust and fast skew detection algorithm based on hierarchical Hough transform is proposed. It is capable of detecting the skew angle for various document images, including technical articles, postal labels, handwritten text, forms, drawings and bar codes. The algorithm is robust even when black margins introduced by photocopying are present in the image and when the document is scanned at a low resolution of 50 dpi. The algorithm consists of two steps. In the first step we quickly extract the centroids of connected components using a graph data structure. Then, a hierarchical Hough transform (at two different angular resolutions) is applied to the selected centroids. The skew angle corresponds to the location of the highest peak in the Hough space. The performance of the algorithm is shown on a number of document images collected from various application domains. The algorithm is not very sensitive to algorithmic parameters. For an A4 size document image scanned at 50 dpi (typically 413 x 575 pixels), our algorithm is able to detect the skew angle with an accuracy of 0.1 degrees in 0.4s of CPU time on a SunSparc 20 workstation. Copyright (C) 1996 Pattern Recognition Society.

关键词： skew detection document image processing hierarchical Hough transform block adjacency graph connected components

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Classification of documents by form and content

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PATTERN RECOGNITION LETTERS 1997年第11-13期18卷 1225-1231页

作者： Maderlechner, G Suda, P Bruckner, T Siemens AG Corp Res & Dev D-81730 Munchen Germany

This paper presents a modular software system, which classifies a large variety of office documents according to layout form and textual content. It consists of the following components: layout analysis, pre-classification, OCR interface, fuzzy string matching, text categorization, lexical, syntactical and semantic analysis. The system has been applied to the following tasks: presorting of forms, reports and letters, index extraction for archiving and retrieval, page type classification and text column analysis of real estate register documents, in-house mail sorting and electronic distribution to departments. The architecture, modules, and practical results are described. (C) 1997 Elsevier Science B.V.

关键词： document analysis document archiving and retrieval document segmentation classification text classification layout analysis document image processing

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Handwritten Hindi character recognition: a review

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IET image processing 2018年第11期12卷 1919-1933页

作者： Yadav, Madhuri Purwar, Ravindra Kumar Mittal, Mamta Guru Govind Singh Indrapratha Univ USIC&T Delhi India GB Panth Govt Engn Coll Dept Comp Sci & Engn Delhi India

As the years passed by, computers became more powerful and automation became the need of generation. Humans tried to automate their work and replace themselves with machines. This effort of transition from manual to automatic gave rise to various research fields, and document character recognition is one such field. From the last few years, there is a sincere contribution from researchers for the development of optical character recognition systems for various scripts and languages. As a result of intensive research and development, there has been a significant improvement in handwritten devnagari text recognition. The main focus of this study is detailed survey of existing techniques for recognition of offline handwritten Hindi characters. It addresses all the aspects of Hindi character recognition starting from database to various phases of character recognition. The most relevant techniques of preprocessing, feature extraction and classification are discussed in various sections of this study. Moreover, this study is a zest of work accepted and published by research community in recent years. This study benefits its readers by discussing limitations of existing techniques and by providing beneficial directions of research in this field.

关键词： document image processing feature extraction image classification natural language processing optical character recognition text analysis

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Parameter-free based two-stage method for binarizing degraded document images

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PATTERN RECOGNITION 2012年第12期45卷 4250-4262页

作者： Chiu, Yung-Hsiang Chung, Kuo-Liang Yang, Wei-Ning Huang, Yong-Huai Liao, Chi-Huang Natl Taiwan Univ Sci & Technol Dept Comp Sci & Informat Engn Taipei 10607 Taiwan Natl Taiwan Univ Sci & Technol Dept Informat Management Taipei 10607 Taiwan Jinwen Univ Sci & Technol Inst Comp & Commun Engn New Taipei City 23154 Taiwan Syst Online Co Ltd 8F Taipei 10654 Taiwan

Binarization plays an important role in document image processing, especially in degraded documents. For degraded document images, adaptive binarization methods often incorporate local information to determine the binarization threshold for each individual pixel in the document image. We propose a two-stage parameter-free window-based method to binarize the degraded document images. In the first stage, an incremental scheme is used to determine a proper window size beyond which no substantial increase in the local variation of pixel intensities is observed. In the second stage, based on the determined window size, a noise-suppressing scheme delivers the final binarized image by contrasting two binarized images which are produced by two adaptive thresholding schemes which incorporate the local mean gray and gradient values. Empirical results demonstrate that the proposed method is competitive when compared to the existing adaptive binarization methods and achieves better performance in precision, accuracy, and F-measure. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Adaptive binarization method Degraded document image document image processing Performance evaluation

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Subspace Models for document Script and Language Identification

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INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY 2010年第2期20卷 140-148页

作者： Vikram, T. N. Gowda, K. Chidananda Univ Caen GREYC F-14050 Caen France Univ Mysore Int Sch Informat Management Mysore Karnataka India

In this article, we explore the suitability of subspace models like 2DPCA [Yang et al., IEEE Trans Pattern Anal Machine Intelligence 26 (2004), 131-137], 2DFLD [Yang et al., Pattern Recogn 38 (2005), 1125-1129], etc. for document script and language identification. They are employed to identify language and script at both paragraph and word level. Elaborate experimentation has been conducted which has revealed that they are robust enough to handle highly confusing scripts and their performance does not degrade drastically even in the presence of noise. A generic language identification has been attempted in this work, to identify languages of both Asian and European origin by considering a dataset of 20 different languages. (C) 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 140-148, 2010;Published online in Wiley Inter Science (***). DOI 10.1002/ima.20215

关键词： script identification language identification subspace models 2DPCA 2DFLD OCR document image processing

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SIFT and HOG features for the retrieval of ancient Kannada epigraphs

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IET image processing 2020年第17期14卷 4657-4662页

作者： Parashivamurthy, Ravi Naveena, Chikkaguddaiah Kumar, Yeliyur Hanumathiah Sharath SJB Inst Technol Dept Comp Sci & Engn Bengaluru Karnataka India Vidyavardhaka Coll Engn Dept Comp Sci & Engn Mysuru Karnataka India Maharaja Inst Technol Dept Informat Sci & Engn Mysuru Karnataka India Visvesvaraya Technol Univ Belagavi Karnataka India

In this work, the authors presented the indexing method for efficient retrieval of Kannada characters. Here the characters were segmented by the connected component method. Then features were extracted by scale invariant feature transform (SIFT) and histogram of oriented gradients (HOG) methods. These features were condensed by principal component analysis. They presented the indexing approach using K-dimensional tree (K-D tree) to improve the identification process. For the experiment, they used their own database. The results of the experiment show that the indexing prior is faster than conventional identification approaches in terms of time to script. From experimentation, they observe that fusion features achieve the maximum accuracy of 90% with varying principal component analysis features.

关键词： feature extraction image classification principal component analysis transforms image segmentation history trees (mathematics) indexing image retrieval natural language processing document image processing K-dimensional tree K-D tree identification process fusion features principal component analysis features ancient Kannada epigraphs indexing method Kannada characters connected component method scale invariant feature HOG indexing approach histogram of oriented gradients methods

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