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International Workshop on Frontiers in Handwriting Recognition

作者： Yann Leydier Jean Duong Stéphane Brés Véronique Églin Frank Lebourgeois Martial Tola CoReNum France Universite de Lyon Lyon Auvergne-RhÃ´ne-Alpes FR CNRS INSA-Lyon Université de Lyon France

ISBN: (纸本)9781509009824

In this paper we introduce libcrn, a multiplatform open-source document image processing library aimed at researchers and companies. It is written in C++11 and has a non-contaminating license that makes it available for use in any project without legal constraints. The features include low-level image processing (color format conversion, binarization, convolution, PDE...), document images specific tools (connected components extraction, recursive block description, PDF export...), maths (matrix arithmetics, linear algebra, GMMs, equation solvers...), classification and clustering (kNN, k-means, HMMs...). The API is comprehensively documented and libcrn's architecture follows modern C++ guidelines to facilitate the handling of the library and enforce its safe usage. A sample OCR, which is only 30 lines long, is described to illustrate libcrn's scope of possibilities.

关键词： Feature extraction Libraries Shape Tensile stress document image processing C++ languages

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TABS-a new software framework for document image processing, analysis, and understanding

TABS-a new software framework for document image processing,...

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International Conference on document Analysis and Recognition

作者： C. Cracknell A.C. Downton L. Du Department of Electronic Systems Engineering University of Essex Colchester UK

This paper provides an overview of a new software framework TABS, which has been designed to support the rapid development of image processing and image analysis systems and components. Compared to other image manipulation software frameworks, TABS has a number of novel features which make it particularly suitable for use in applications where hypotheses rather than single "hard" results are generated by system components, and symbolic data are manipulated.

关键词： document image processing image analysis Programming environments image processing Libraries image storage Design engineering Systems engineering and theory Software design Application software

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Building a paperless office with document image processing system

Building a paperless office with document image processing s...

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International Conference on Professional Communication (IPCC)

作者： T.T. Lau Research Library Hewlett Packard Laboratories Palo Alto CA USA

The DIP (document image processing) system, and its configurations and functions are described, and the standards issue facing the DIP system is discussed. DIP involves scanning and electronically storing documents so they can be retrieved and used without requiring paper copies or file cabinets. DIP systems are most useful when integrated into a local area network that provides shared access to devices such as laser printers, scanners, and optical disks.< >

关键词： document image processing Electronics packaging image storage Optical character recognition software image retrieval image processing Workstations image databases Computer displays Local area networks

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FIRST MAURDOR 2013 EVALUATION CAMPAIGN IN SCANNED document image processing

FIRST MAURDOR 2013 EVALUATION CAMPAIGN IN SCANNED DOCUMENT I...

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IEEE International Conference on Acoustics, Speech and Signal processing

作者： Ilya Oparin Juliette Kahn Olivier Galibert LNE Laboratoire national de metrologie et d'essais National Metrology and Testing Laboratory France

ISBN: (纸本)9781479928941

This paper presents the results of the first Maurdor evaluation campaign. This campaign aims at evaluating the complete chain of scanned document image processing. It has a modular structure that includes page segmentation and zone classification, identification of writing type and language, optical character recognition and revealing logical structure of a document. This campaign is based on a unique corpus of 8,000 images of scanned documents annotated at different levels. Presentation of the results of the first campaign is important to assess the state-of-the-art and create common references both for participants in future campaigns and, as the scoring tools are publicly available, for independent tests.

关键词： document image processing campaign life image processing MODULAR CONSTRUCTIONS logical architecture optical character recognition First Character recognition

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iDocChip - A Configurable Hardware Architecture for Historical document image processing: Text Line Extraction

iDocChip - A Configurable Hardware Architecture for Historic...

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International Conference on Reconfigurable Computing and FPGAs (ReConFig)

作者： Menbere Kina Tekleyohannes Vladimir Rybalkin Muhammad Mohsin Ghaffar Norbert Wehn Andreas Dengel Microelectronic Systems Design Research Group University of Kaiserslautern Germany German Research Center for Artificial Intelligence (DFKI) Kaiserslautern Germany

ISBN: (纸本)9781728119588

Digitizing historical archives poses a great challenge due to the quality degradation existing in these documents. Hence, even well-established Optical Character Recognition (OCR) systems, such as Abby, OCRopus, Tesseract, etc., fail to give sufficient recognition accuracy for historical archives, since they are optimized for transcribing contemporary documents. In contrast, the open-source anyOCR system is designed specifically for digitizing historical documents with state-of-the-art image processing techniques, to achieve high accuracy. Nowadays, the retrieval of historical document images for further OCR requires special scanning devices that are bulky and stationary. As a result, a portable device that combines scanning and OCR capabilities is beneficial to transcribe documents without the need to remove them from where they are archived. For example, smart goggles equipped with embedded OCR device can be used for instant word spotting. However, the available anyOCR software implementation has long runtime and high power consumption. As a solution, we propose a low power, energy-efficient accelerator with real-time capabilities called iDocChip, which is a hybrid hardware-software programmable System-on-Chip (SoC) for digitizing historical documents. This chip can be easily integrated in a portable device. This paper focuses on one of the most crucial processing steps in anyOCR: text line extraction. We propose, to the best of our knowledge, the first hybrid hardware-software architecture of the text line extraction technique implemented on an FPGA based programmable SoC. The resulting custom hardware accelerator outperforms the existing anyOCR software implementation by 120×, while achieving 1700× higher energy efficiency without affecting the high accuracy of the system.

关键词： document image processing embedded systems feature extraction field programmable gate arrays optical character recognition software architecture system-on-chip text analysis optical character recognition document image processing Field programmable gate arrays text processing Software architecture system-on-chip document image Embedded systems Feature extraction Portable equipment digitization

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Hierarchical content classification and script determination for automatic document image processing

Hierarchical content classification and script determination...

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International Conference on Pattern Recognition

作者： Qing Wang Zheru Chi Rongchun Zhao Centre for Mu(timedia Signal Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China Department of Computer Science and Engineering Northwestern Polytechnical University Xi''an China

ISBN: (纸本)076951695X

Page segmentation and image content classification plays an important role in automatic document image processing with applications to mixed-type document image compression, form and check reading, and automatic mail sorting. We propose an enhanced background-thinning based page segmentation algorithm to process document images rapidly and eliminate some small regions embedded in other regions. We then present a hierarchical approach, which combines the cross correlation measure, Kolmogorov complexity measure, and a neural network, to classify sub-images into halftones and texts. The approach also achieves high accuracy in text determination using a three-layer feed-forward network where the text region can be classified into Chinese or alphabetic characters. Experimental results on a number of mixed-type document images show the efficiency and effectiveness of our approach.

关键词： document image processing image segmentation image analysis Postal services Neural networks image converters Application software Character recognition Computer science Signal processing

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image processing based Degraded Camera Captured document Enhancement for Improved OCR Accuracy 6

Image Processing based Degraded Camera Captured Document Enh...

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6th International Conference on Cloud System and Big Data Engineering (Confluence)

作者： Sharma, Pooja Sharma, Shanu Amity Univ Dept Comp Sci & Engn Noida Uttar Pradesh India

ISBN: (纸本)9781467382038

Over the past decade the document analysis and processing related to camera based document images has gained the interest of research community. Nowadays, cameras are easily available in the smart phones that can be carried in the small space of our pockets while being lightweight, portable and relieving us from the burden of walking down to a scanner for a digital copy of a document. But even though capturing a document image through a phone camera appears simple, the chances of obtaining a perfect picture are scanty. As when the picture is captured in an unconstrained environment, there are chances of degradation to creep in that will hamper the visual quality of the document image which further effect the readability( in terms of OCR accuracy). Low quality documents give poor results. document images contain various degradations such as blur, uneven illumination, perspective distortion, low resolution, smear etc. Quality enhancement is helpful to recognize a camera captured document more accurately and if not completely removing the degradations, it can be used for suppressing them and making the text more readable. This paper evaluates the performance of various de-blurring techniques for noisy and blurred camera captured documents.

关键词： Camera captured documents document image processing OCR accuracy quality enhancement

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Performance evaluation methodology for document image dewarping techniques

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IET image processing 2012年第6期6卷 738-745页

作者： Stamatopoulos, N. Gatos, B. Pratikakis, I. Natl Ctr Sci Res Demokritos Inst Informat & Telecommun GR-15310 Athens Greece Natl & Kapodistrian Univ Athens Dept Informat & Telecommun Athens Greece Democritus Univ Thrace Dept Elect & Comp Engn GR-67100 Xanthi Greece

The performance evaluation of dewarping techniques is currently addressed by concentrating in visual pleasing impressions or by using optical character recognition (OCR) as a means for indirect evaluation. In this study, the authors present a performance evaluation methodology that calculates a comprehensive evaluation measure which reflects the entire performance of a dewarping technique in a concise quantitative manner. The proposed evaluation measure takes into account the deviation of the dewarped text lines from a horizontal straight reference which is considered to be the optimal result. This measure is expressed by the integral over the dewarped text line curves. To reduce the manual effort for identifying the text lines in the dewarped image, the authors propose a point-to-point matching procedure that finds the correspondence between the manually marked warped document image and the dewarping counterpart. This enables an evaluation for unlimited number of methodologies addressing a marking procedure which is applied only once. The validity of the proposed performance evaluation methodology is demonstrated by a concise experimental work that comprises four state-of-the-art dewarping techniques as well as the involvement of different users in the interactive part of the procedure.

关键词： text line identification point-to-point matching procedure image matching image recognition dewarped text line curve horizontal straight reference Computer vision and image processing techniques warped document image optical character recognition document image dewarping technique text analysis document processing techniques document image processing visual pleasing impression comprehensive evaluation measure

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Robust image authentication scheme with self-repair capability for greyscale source document images via PNG format

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IET image processing 2016年第12期10卷 971-978页

作者： Wang, Feng Lyu, Wan-Li Pan, Jeng-Shyang Fujian Univ Technol Coll Math & Phys Fujian Prov Key Lab Big Data Min & Applicat Fuzhou 350118 Fujian Peoples R China Fujian Normal Univ Sch Math & Comp Sci Fujian Prov Key Lab Network Secur & Cryptol Fuzhou 350117 Fujian Peoples R China Anhui Univ Sch Comp Sci & Technol Minist Educ Key Lab Intelligent Comp & Signal Proc Hefei 230039 Peoples R China Fujian Univ Technol Coll Informat Sci & Engn Fujian Prov Key Lab Big Data Min & Applicat Fuzhou 350118 Fujian Peoples R China

Recently, Lee and Tsai proposed a new authentication method for greyscale document images using the portable network graphics format image;however, their method cannot resist the self-substitution attack, the same-position-substitution attack, or the cut-off attack. Furthermore, those attacks can be completed by the popular image editing software Adobe Photoshop. Therefore, the authors proposed a security-enhanced authentication scheme based on Lee and Tsai's method. The authors' proposed scheme uses three random binary sequences to randomise the binary version of a given greyscale document image, and thus overcomes the security flaws mentioned above. The authors' proposed scheme is capable of repairing the content of the given stego-image if attacked by the methods mentioned above. Moreover, the authors' proposed scheme retains all of the strengths of Lee and Tsai's scheme. The authors improve the opacity of the alpha channel of stego-image by using Wang and Su's extended secret sharing, and enhance the data security by using Hash functions. The experimental results show that the authors' proposed scheme is effective for application.

关键词： document image processing steganography random sequences binary sequences cryptography robust image authentication scheme self-repair capability greyscale source document images PNG format portable network graphics format image self-substitution attack same-position-substitution attack cut-off attack image editing software Adobe Photoshop security-enhanced authentication scheme random binary sequences stego-image hash functions

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A screen-shooting resilient document image watermarking scheme using deep neural network

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IET image processing 2023年第2期17卷 323-336页

作者： Ge, Sulong Fei, Jianwei Xia, Zhihua Tong, Yao Weng, Jian Liu, Jianan Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing Peoples R China Nanjing Univ Informat Sci & Technol Engn Res Ctr Digital Forens Nanjing Peoples R China Jinan Univ Coll Cyber Secur Guangzhou Peoples R China Guangzhou Fongwell Data Ltd Co Guangzhou Peoples R China

With the advent of the screen-reading era, the confidential documents displayed on the screen can be easily captured by a camera without leaving any traces. Thus, this paper proposes a novel screen-shooting resilient watermarking scheme for document image using deep neural network. By applying this scheme, when the watermarked image is displayed on the screen and captured by a camera, the watermark can be still extracted from the captured photographs. Specifically, the scheme is an end-to-end neural network with an encoder to embed watermark and a decoder to extract watermark. During the training process, a distortion layer between encoder and decoder is added to simulate the distortions introduced by screen-shooting process in real scenes, such as camera distortion, shooting distortion, and light source distortion. Furthermore, a background sensitive loss and a lpips loss are used to improve visual quality of the watermarked document images in the training process. Besides, a strength factor adjustment strategy is also designed to improve the visual quality with little loss of bit extraction accuracy. The experimental results show that the proposed scheme has higher visual quality and robustness than the other two recent state-of-the-art methods.

关键词： feature extraction shooting distortion background sensitive loss camera distortion screen-shooting resilient document image watermarking distortion layer document processing and analysis techniques image and video coding bit extraction Neural nets image watermarking Computer vision and image processing techniques strength factor adjustment end-to-end neural network confidential documents deep learning (artificial intelligence) document image processing Data security deep neural network watermark extraction lpips loss light source distortion screen-reading era visual quality

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