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Electronic reading of graphic documents - Belarusian work in document recognition

COMPUTING & CONTROL ENGINEERING JOURNAL 1996年第4期7卷 185-192页

作者： Ablameyko, S Inst. of Eng. Cybern. Acad. of Sci. Minsk Byelorussia

Graphics recognition which includes document and line-drawing interpretation is one of the important and difficult fields of image analysis. This article describes work and results of Belarusian scientists in this field. The main scientific and practical achievements are given, Our integration into the world scientific community as well as benefits for both sides are also described.

关键词： image recognition world scientific community electronic reading document image processing image representation Belarusian work graphic documents Pattern recognition and computer vision equipment Spatial and pictorial databases image scanners Optical information, image and video signal processing line drawing interpretation document recognition Computer vision and image processing techniques document processing techniques image analysis

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Designing and evaluating a system of document recognition to support interoperability among collaborative enterprises

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COMPUTERS IN INDUSTRY 2013年第5期64卷 598-608页

作者： Wajid, Usman Namoun, Abdallah Marin, Cesar A. Mehandjiev, Nikolay Univ Manchester Manchester M15 6PB Lancs England

A common understanding of business documents is important for realizing interoperability among collaborating enterprises. In this paper we report on the design and evaluation of a system that can help collaborating enterprises to efficiently recognise and align business documents (e.g. incoming emails and attachments) according to the enterprises' local document repository. The system relies on the interplay between automatic recognition of business documents and human intervention by means of an assistive mapping tool. Our findings show that the balance between automatic recognition and human intervention ensures greater levels of accuracy in the system. We evaluate our system from both usability and accuracy perspectives and argue that some of the lessons learned and design decisions we took are applicable to the general mixed initiative tools for end user support. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Enterprise interoperability document recognition

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Rejection measurement based on linear discriminant analysis for document recognition

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INTERNATIONAL JOURNAL ON document ANALYSIS AND recognition 2011年第3期14卷 263-272页

作者： He, Chun Lei Lam, Louisa Suen, Ching Y. Concordia Univ Dept Comp Sci & Software Engn CENPARMI Ctr Pattern Recognit & Machine Intellige Montreal PQ H3G 1M8 Canada

In document recognition, it is often important to obtain high accuracy or reliability and to reject patterns that cannot be classified with high confidence. This is the case for applications such as the processing of financial documents in which errors can be very costly and therefore far less tolerable than rejections. This paper presents a new approach based on Linear Discriminant Analysis (LDA) to reject less reliable classifier outputs. To implement the rejection, which can be considered a two-class problem of accepting the classification result or otherwise, an LDA-based measurement is used to determine a new rejection threshold. This measurement (LDAM) is designed to take into consideration the confidence values of the classifier outputs and the relations between them, and it represents a more comprehensive measurement than traditional rejection measurements such as First Rank Measurement and First Two Ranks Measurement. Experiments are conducted on the CENPARMI database of numerals, the CENPARMI Arabic Isolated Numerals Database, and the numerals in the NIST Special Database 19. The results show that LDAM is more effective, and it can achieve a higher reliability while maintaining a high recognition rate on these databases of very different origins and sizes.

关键词： document recognition Linear discriminant analysis Rejection criterion recognition reliability

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Low resolution, degraded document recognition using neural networks and hidden Markov models

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PATTERN recognition LETTERS 1998年第3-4期19卷 365-371页

作者： Schenkel, M Jabri, M Univ Sydney Sydney NSW 2006 Australia

We collected a large, real world database, containing degraded, old and fared documents and present a comparison between two leading edge commercial software packages and human reading performance which shows quantitatively the huge performance gap between humans and machines, even on random character documents where no context can be used. This indicates room for possible improvements. We implemented an integrated segmentation and recognition algorithm using neural networks and hidden Markov models trained on the database and present results which show the superior performance of the algorithm. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： OCR document recognition low resolution neural networks hidden Markov models

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Gradient-based learning applied to document recognition

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PROCEEDINGS OF THE IEEE 1998年第11期86卷 2278-2324页

作者： Lecun, Y Bottou, L Bengio, Y Haffner, P AT&T Bell Labs Res Speech & Image Proc Serv Res Lab Red Bank NJ 07701 USA Univ Montreal Dept Informat & Rech Operat Montreal PQ H3C 3J7 Canada

Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient-based learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify high-dimensional patterns, arch as handwritten characters, with minimal preprocessing. This paper reviews various methods applied to handwritten character recognition and compares them on a standard handwritten digit recognition task. Convolutional neural networks, which are specifically designed to deal with the variability of two dimensional (2-D) shapes, are shown to outperform all other techniques. Real-life document recognition systems are composed of multiple modules including field extraction, segmentation recognition and language modeling. A new learning paradigm, called graph transformer networks (GTN's), allows such multimodule systems to be trained globally using gradient-based methods so;as to minimize an overall performance measure. Two systems for online handwriting recognition are described. Experiments demonstrate the advantage of global training, and the flexibility of graph transformer networks. A graph transformer network for reading a bank check is also described It uses convolutional neural network character recognizers combined with global training techniques to provide record accuracy on business and personal checks. It is deployed commercially and reads several million checks per day.

关键词： convolutional neural networks document recognition finite state transducers gradient-based learning graph transformer networks machine learning neural networks optical character recognition (OCR)

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Tibetan Historical document recognition of Uchen Script using Baseline Information 10

Tibetan Historical Document Recognition of Uchen Script usin...

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10th International Conference on Graphics and Image Processing (ICGIP)

作者： Li, Zhenjiang Wang, Weilan Northwest Minzu Univ Minist Educ Key Lab Chinas Ethn Languages & Informat Technol Lanzhou Gansu Peoples R China

ISBN: (数字)9781510628298

ISBN: (纸本)9781510628298

A method is proposed for recognition of uchen script Tibetan historical document using baseline information. The baseline is a significant feature of uchen script Tibetan characters, and the result of Tibetan document recognition can be improved effectively by using baseline information. Firstly, the baseline is detected accurately by the upper edge of character strokes in the document. Secondly, the baseline is used for segmentation of text line and character, and the text line adhesion can be handled also. Finally, the character part above baseline and that below baseline are recognized individually, and the final results are synthesized. The experiment shows that the proposed method is effective for the recognition of Tibetan historical document, and the recognition accuracy is better than that of the whole character recognition.

关键词： Uchen script Tibetan historical document baseline segmentation of text line and character document recognition

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Printed Arabic document recognition system

Printed Arabic document recognition system

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Conference on document recognition and Retrieval XII

作者： Jin, JM Wang, H Ding, XQ Peng, LR Tsinghua Univ Dept Elect Engn State Key Lab Intelligent Technol & Syst Beijing 100084 Peoples R China

ISBN: (纸本)0819456497

As a cursive script, the characteristics of Arabic texts are different from those of Latin or Chinese greatly. For example, an Arabic character has up to four written forms and characters that can be joined are always connected on the baseline. Therefore, the methods used for Arabic document recognition are different from those for Latin and Chinese, where the segmentation of Arabic characters is the most critical problem. In this paper, a printed Arabic document recognition system is presented, which is composed of text line segmentation, word segmentation, character segmentation, character recognition and post-processing stages. Experiment shows that the recognition accuracy of the system has achieved 97.62%.

关键词： document recognition character recognition character segmentation line segmentation post-processing Arabic script

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Determining Optimal Frame Processing Strategies for Real-Time document recognition Systems 16th

Determining Optimal Frame Processing Strategies for Real-Tim...

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16th IAPR International Conference on document Analysis and recognition (ICDAR)

作者： Bulatov, Konstantin Arlazarov, Vladimir V. Russian Acad Sci Fed Res Ctr Comp Sci & Control Moscow Russia Smart Engines Serv LLC Moscow Russia

ISBN: (纸本)9783030863319

Mobile document analysis technologies became widespread and important, and growing reliance on the performance of critical processes, such as identity document data extraction and verification, lead to increasing speed and accuracy requirements. Camera-based documents recognition on mobile devices using video stream allows to achieve higher accuracy, however in real time systems the actual time of individual image processing needs to be taken into account, which it rarely is in the works on this subject. In this paper, a model of real-time document recognition system is described, and three frame processing strategies are evaluated, each consisting of a per-frame recognition results combination method and a dynamic stopping rule. The experimental evaluation shows that while full combination of all input results is preferable if the frame recognition time is comparable with frame acquisition time, the selection of one best frame based on an input quality predictor, or a combination of several best frames, with the corresponding stopping rule, allows to achieve higher mean recognition results accuracy if the cost of recognizing a frame is significantly higher than skipping it.

关键词： Mobile recognition Real-time recognition Video stream Anytime algorithms document recognition

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A symbol classifier able to reject wrong shapes for document recognition systems

A symbol classifier able to reject wrong shapes for document...

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3rd International Workshop on Graphics recognition (GREC 99)

作者： Anquetil, É Coüasnon, B Dambreville, F IRISA INSA Dept Informat F-35043 Rennes France

ISBN: (纸本)3540412220

We propose in this paper a new framework to develop a transparent classifier able to deal with reject notions. The generated classifier can be characterized by a strong reliability without loosing good properties in generalization. We show on a musical scores recognition system that this classifier is very well suited to develop a complete document recognition system. Indeed this classifier allows them firstly to extract known symbols in a document (text for example) and secondly to validate segmentation hypotheses. Tests had been successfully performed on musical and digit symbols databases.

关键词： document recognition symbol recognition musical score classification genetic algorithm radial basis function neural networks reliability

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Color Correction of the document Owner's Photograph Image during recognition on Mobile Device 13

Color Correction of the Document Owner's Photograph Image du...

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13th International Conference on Machine Vision

作者： Polevoy, D., V Panfilova, E., I Ershov, E., I Nikolaev, D. P. Smart Engines Serv LLC Moscow Russia RAS Kharkevich Inst Inst Informat Transmiss Problems Moscow Russia RAS Fed Res Ctr Comp Sci & Control Moscow Russia RAS VA Trapeznikov Inst Control Sci Moscow Russia Natl Univ Sci & Technol MISIS Moscow Russia Moscow Inst Phys & Technol Dolgoprodny Russia

ISBN: (纸本)9781510640412

The growing popularity of mobile services increases the risks of financial and other losses from fraudulent user actions. To reduce the number of illegal actions and comply with the law when using mobile services, it is often scheme that user presents it's identity document. In case of remote access via a mobile device, this means receiving and analyzing a video of a document image. One of the criteria for the authenticity of the captured security document is the presence of security optically variable devices (kinegrams, holograms). Reliable determination of the presence or absence of such security elements from video stream frames is greatly complicated by changes in color between frames. The paper discusses the possibility of using a priori information about the monochrome photograph of the document owner to compensate changes in color between frames. Color distributions are investigated on the example of black-and-white photographs. A new method for automatic white balance correction is proposed. The results of the method are tested on real data obtained with a mobile device.

关键词： White balance digital image color correction optically variable device detection document recognition

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