检索结果-内蒙古大学图书馆

作者： Made Windu Antara Kesiman Universite de La Rochelle

学位级别：博士

The collection of palm leaf manuscripts is an important part of Southeast Asian people's culture and life. Following the increasing of the digitization projects of heritage docu- ments around the world, the collection of palm leaf manuscripts in Southeast Asia finally attracted the attention of researchers in document image analysis (DIA). The research work conducted for this dissertation focused on the heritage documents of the collec- tion of palm leaf manuscripts from Indonesia, especially the palm leaf manuscripts from Bali. This dissertation took part in exploring DIA researches for palm leaf manuscripts collection. This collection offers new challenges for DIA researches because it uses palm leaf as writing media and also with a language and script that have never been analyzed before. Motivated by the contextual situations and real conditions of the palm leaf ma- nuscript collections in Bali, this research tried to bring added value to digitized palm leaf manuscripts by developing tools to analyze, to transliterate and to index the content of palm leaf manuscripts. These systems aim at making palm leaf manuscripts more acces- sible, readable and understandable to a wider audience and, to scholars and students all over the world. This research developed a DIA system for document images of palm leaf manuscripts, that includes several image processing tasks, beginning with digitization of the document, ground truth construction, binarization, text line and glyph segmentation, ending with glyph and word recognition, transliteration and document indexing and re- trieval. In this research, we created the first corpus and dataset of the Balinese palm leaf manuscripts for the DIA research community. We also developed the glyph recognition system and the automatic transliteration system for the Balinese palm leaf manuscripts. This dissertation proposed a complete scheme of spatially categorized glyph recognition for the transliteration of Balinese palm leaf manuscript

关键词： palm leaf manuscripts Balinese script document image analysis dataset binarization text line segmentation glyph recognition transliteration

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Twenty years of document image analysis in PAMI

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IEEE TRANSACTIONS ON PATTERN analysis AND MACHINE INTELLIGENCE 2000年第1期22卷 38-62页

作者： Nagy, G Rensselaer Polytech Inst Troy NY 12180 USA

The contributions to document image analysis of 99 papers published in the IEEE Transactions on Pattern analysis and Machine Intelligence (PAMI) are clustered, summarized, interpolated, interpreted, and tactfully eval... 详细信息

关键词： document image analysis image processing OCR character recognition forms processing graphics recognition

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Parallel preprocessing algorithms for document image analysis

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JOURNAL OF THE INSTITUTION OF ELECTRONICS AND TELECOMMUNICATION ENGINEERS 1996年第3期42卷 165-173页

作者： Rao, PS Srinivas, C Chand, BH Agarwal, A Department of Computer/Information Sciences University of Hyderabad Hyderabad 500 046 India

This paper presents the parallel implementation of sequential algorithms for skew estimation, connected components generation and smearing on a hypercube architecture, These algorithms have been tested on PARAM CAMPUS... 详细信息

关键词： skew connected components MBRs smearing document image analysis parallel algorithms

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Digital geometric methods in document image analysis

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PATTERN RECOGNITION 1999年第3期32卷 407-424页

作者： Gross, A Latecki, LJ CUNY Grad Ctr Dept Comp Sci Computat Vis & Percept Lab Flushing NY 11367 USA CUNY Queens Coll Flushing NY 11367 USA Univ Hamburg Dept Comp Sci D-22527 Hamburg Germany

One of the main tasks of digital image analysis is to recognize the properties of real objects based on their digital images. These: images are obtained by some sampling device, like a CCD camera, and are represented as finite sets of points that are assigned some value in a gray level or color scale. A Fundamental question in image understanding is which features in the digital image correspond, under a given set of conditions, to certain properties of the underlying objects. In many practical applications this question is answered empirically by visually inspecting the digital images. In this paper. we present a mathematically comprehensive answer to this question with respect to topological properties. In particular., we derive conditions relating properties of real objects to the grid size of the sampling device which guarantee that a real object and its digital image are topologically equivalent. These conditions also imply that two digital images of a given object are topologically equivalent. Moreover, we prove that a topologically invariant digitization must result in well-composed or strongly connected sets and that only certain local neighborhoods are realizable for such a digitization. Using the derived topological model of a well-composed digital image, we demonstrate the effectiveness of this model with respect to the digitization, thresholding, correction, and compression of digital document images. (C) 1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

关键词： digital topology digital geometry topologically invariant digitization document image analysis well-composed sets topological compression

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Turning document image analysis Methods into Web Services - An Example Using OCRopus 1

Turning Document Image Analysis Methods into Web Services - ...

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14th IAPR International Conference on document analysis and Recognition (ICDAR)

作者： Wuersch, Marcel Simistira, Foteini Ingold, Rolf Liwicki, Marcus Univ Fribourg Document Image & Voice Anal Grp Bd Perolles 90 CH-1700 Fribourg Switzerland TU Kaiserslautern MindGarage Kaiserslautern Germany

ISBN: (纸本)9781538635865

Research in document image analysis is producing a vast amount of good methods for the different research tasks. Though, it still remains difficult to reproduce experiments, integrate existing methods into other research projects, or build software solutions combining different methods together. This paper focuses on two points: (i) we reason why providing access to methods as Web Services can solve many of these problems, and (ii) we show how an existing open-source method can be transformed into a Web Service and used using the well-known open-source package OCRopus as an example. The processes explained can be performed by anyone who would like to provide their methods as Web Services.

关键词： document image analysis Web Services Handwritten Text Recognition Optical Character Recognition OCRopus

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DIVA-DAF: A Deep Learning Framework for Historical document image analysis 23

DIVA-DAF: A Deep Learning Framework for Historical Document ...

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7th International Workshop on Historical document Imaging and Processing (HIP)

作者： Vogtlin, Lars Scius-Bertrand, Anna Maergner, Paul Fischer, Andreas Ingold, Rolf Univ Fribourg Fribourg Switzerland

ISBN: (纸本)9798400708411

Deep learning methods have shown strong performance in solving tasks for historical document image analysis. However, despite current libraries and frameworks, programming an experiment or a set of experiments and executing them can be time-consuming. This is why we propose an open-source deep learning framework, DIVA-DAF, which is based on PyTorch Lightning and specifically designed for historical document analysis. Pre-implemented tasks such as segmentation and classification can be easily used or customized. It is also easy to create one's own tasks with the benefit of powerful modules for loading data, even large data sets, and different forms of ground truth. The applications conducted have demonstrated time savings for the programming of a document analysis task, as well as for different scenarios such as pre-training or changing the architecture. Thanks to its data module, the framework also allows to reduce the time of model training significantly.

关键词： deep learning framework document image analysis historical documents deep neural networks

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LayoutParser: A Unified Toolkit for Deep Learning Based document image analysis 16th

LayoutParser: A Unified Toolkit for Deep Learning Based Docu...

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16th IAPR International Conference on document analysis and Recognition (ICDAR)

作者： Shen, Zejiang Zhang, Ruochen Dell, Melissa Lee, Benjamin Charles Germain Carlson, Jacob Li, Weining Allen Inst AI Seattle WA 98103 USA Brown Univ Providence RI 02912 USA Harvard Univ Cambridge MA 02138 USA Univ Washington Seattle WA 98195 USA Univ Waterloo Waterloo ON Canada

ISBN: (纸本)9783030865498

Recent advances in document image analysis (DIA) have been primarily driven by the application of neural networks. Ideally, research outcomes could be easily deployed in production and extended for further investigation. However, various factors like loosely organized codebases and sophisticated model configurations complicate the easy reuse of important innovations by a wide audience. Though there have been on-going efforts to improve reusability and simplify deep learning (DL) model development in disciplines like natural language processing and computer vision, none of them are optimized for challenges in the domain of DIA. This represents a major gap in the existing toolkit, as DIA is central to academic research across a wide range of disciplines in the social sciences and humanities. This paper introduces LayoutParser, an open-source library for streamlining the usage of DL in DIA research and applications. The core LayoutParser library comes with a set of simple and intuitive interfaces for applying and customizing DL models for layout detection, character recognition, and many other document processing tasks. To promote extensibility, LayoutParser also incorporates a community platform for sharing both pre-trained models and full document digitization pipelines. We demonstrate that LayoutParser is helpful for both lightweight and large-scale digitization pipelines in realword use cases. The library is publicly available at https://***.

关键词： document image analysis Deep learning Layout analysis Character recognition Open source library Toolkit

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Making DIA Accessible to Non-experts: Designing a Visual Programming Language for document image analysis 2

Making DIA Accessible to Non-experts: Designing a Visual Pro...

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15th IAPR International Conference on document analysis and Recognition (ICDAR) / 2nd International Workshop on Human-document Interaction (HDI)

作者： Rajan, Vinodh Stiehl, H. Siegfried Univ Hamburg Dept Informat Res Grp Image Proc iXMan Lab Hamburg Germany

ISBN: (纸本)9781728150543

The research field of document image analysis (DIA) produces state-of-the-art methods that are intended to analyze digitized documents, a substantial portion of which lie in the realm of humanities. However, applying the methods, more often than not, requires some programming knowledge. This results in low accessibility and, consequently, many of the methods, if not most, are not used by scholars in the humanities. There is a distinct need to bridge this gap and make DIA methods more accessible to end users. In this context, we discuss the design of a Visual Programming Language (VPL) paradigm for an integrated DIA application environment targeting end-users that are not capable of programming. We elucidate in detail the various design considerations that went into the VPL's development and provide a description of our prototype VPL environment, named, AMAP and, finally, discuss future work.

关键词： visual programming visual programming language human-document interaction document image analysis human-computer interaction user-interface design user experience user interface

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Human interactive proofs and document image analysis 5th

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5th International Workshop on document analysis Systems

作者： Baird, HS Popat, K Palo Alto Res Ctr 3333 Coyote Hill Rd Palo Alto CA 94304 USA

ISBN: (纸本)3540440682

The recently initiated and rapidly developing research field of 'human interactive proofs' (HIPs) and its implications for the document image analysis (DIA) research field are described. Over the last five years, efforts to defend Web services against abuse by programs ('bots') have led to a new family of security protocols able to distinguish between human and machine users. AltaVista pioneered this technology in 1997 [Bro01, LBBB01]. By the summer of 2000, Yahoo! and PayPal were using similar methods. In the Fall of 2000, Prof. Manuel Blum of Carnegie-Mellon University and his team, stimulated by Udi Manber of Yahoo!, were studying these and related problems [BAL00]. Soon thereafter a collaboration between the University of California at Berkeley and the Palo Alto Research Center (PARC) built a tool based on systematically generated image degradations [CBF01]. In January 2002, Prof. Blum and the present authors ran the first workshop (at PARC) on HIPs, defined broadly as a class of challenge/response protocols which allow a human to authenticate herself as a member of a given group - e.g. human (vs. machine), herself (vs. anyone else), an adult (vs. a child), etc. All commercial uses of HIPs known to us exploit the gap in ability between human and machine vision systems in reading images of machine printed text. Many technical issues that have been systematically studied by the DIA community are relevant to the HIP research program. This paper describes the evolution of HIP R&D, applications of HIPs now and on the horizon, highlights of the first HIP workshop, and proposals for a DIA research agenda to advance the state of the art of HIPs.

关键词： human interactive proofs document image analysis CAPTCHAs abuse of web sites and services the chatroom problem human/machine discrimination Turing tests OCR performance evaluation document image degradations legibility of text

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SDK Reinvented: document image analysis Methods as RESTful Web Services 12

SDK Reinvented: Document Image Analysis Methods as RESTful W...

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12th IAPR International Workshop on document analysis Systems (DAS)

作者： Wuersch, Marcel Ingold, Rolf Liwicki, Marcus Univ Fribourg DIVA Grp Fribourg Switzerland

ISBN: (纸本)9781509017928

document image analysis (DIA) systems become ever more advanced, but also more complex - computationally, and logically. This increases the difficulty of integrating existing state-of-the-art approaches into new research or into practical workflows. The current approach to sharing software is publishing source code - leaving the burden to the integrator or creating a Software Development Kit (SDK) which is often restricted to one programming language. We present DIVAServices a framework for sharing and accessing DIA methods within the research community and beyond. Using a RESTful web service architecture we provide access to the methods, leading to only one system on which the binaries of methods need to be maintained. All it takes for a developer to use an algorithm is a simple HTTP request with the image data and parameters for the method and they will receive the computed results in a format that allows for seamless integration into any kind of workflow or for further processing. Furthermore, DIVAServices is open-source, enabling other research groups or libraries to host their own instance in their environment. Using this framework, future DIA systems can be built on the shoulders of well tested algorithms, accessible to everyone.

关键词： document image analysis Open Source Web Services

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