2015 13th International Conference on Document Analysis and Recognition (ICDAR)

23-26 Aug. 2015

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  • [Front cover]

    Publication Year: 2015, Page(s): c1
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  • [Back cover]

    Publication Year: 2015, Page(s): c4
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  • Welcome message from honorary chair

    Publication Year: 2015, Page(s): 1
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  • Welcome message from general chairs

    Publication Year: 2015, Page(s): 1
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  • Welcome message from Technical Program Chairs

    Publication Year: 2015, Page(s):1 - 2
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  • Program at a glance

    Publication Year: 2015, Page(s): 1
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  • Conference program

    Publication Year: 2015, Page(s):1 - 40
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  • Table of contents

    Publication Year: 2015, Page(s):i - xv
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  • Author index

    Publication Year: 2015, Page(s):xvi - xxviii
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  • Organizing Committee

    Publication Year: 2015, Page(s):1 - 2
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  • Technical program committee

    Publication Year: 2015, Page(s):1 - 2
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  • Automatic extraction of correlation-entropy features for text document analysis directly in run-length compressed domain

    Publication Year: 2015, Page(s):1 - 5
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2639 KB) | HTML iconHTML

    Automatic feature extraction plays a pivotal role in defining the overall performance of any Document Image Analysis system, which conventionally operates directly over uncompressed images, although most of the real time systems such as fax machines, digital libraries and e-governance applications accrue and archive the documents in the compressed form for the sake of storage and transfer efficien... View full abstract»

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  • A Polar Stroke Descriptor for classification of historical documents

    Publication Year: 2015, Page(s):6 - 10
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1084 KB) | HTML iconHTML

    This paper presents a method for extracting a local scale- and rotation-invariant descriptor called Polar Stroke Descriptor (PSD) from the strokes in handwritten documents. Our descriptor captures the stroke-length distribution on a reference point and results in a robust feature vector. Furthermore, we develop a compact stroke representation termed as strokelets inspired by the classical Bag of W... View full abstract»

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  • Solving substitution ciphers for OCR with a semi-supervised hidden Markov model

    Publication Year: 2015, Page(s):11 - 15
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (592 KB) | HTML iconHTML

    In the past unsupervised HMM training has been applied to solve letter substitution ciphers as they appear in various problems in Natural Language Processing. For some problems, parts of the cipher key can easily be provided by the user, but full manual deciphering would be too time consuming. In this work a semi-supervised HMM deciphering approach that uses partial ground-truth data is introduced... View full abstract»

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  • Co-occurrence Matrix of Oriented Gradients for word script and nature identification

    Publication Year: 2015, Page(s):16 - 20
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (984 KB) | HTML iconHTML

    In this paper, we propose a new scheme for script and nature identification. The objective is to discriminate between machine-printed/handwritten and Latin/Arabic scripts at word level. It is relatively a complex task due to possible use of multi-fonts and sizes, complexity and variation in handwriting. In the proposed script identification system, we extract features from word images using Co-occ... View full abstract»

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  • A recognition based approach for segmenting touching components in Arabic manuscripts

    Publication Year: 2015, Page(s):21 - 25
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1021 KB) | HTML iconHTML

    This work aims to segment touching components (TCs) which may occur between word letters of consecutive text-lines or those of words of the same line in Arabic manuscripts. The proposed approach is mainly based on two steps: 1) finding for a localized touching component its most similar model, stored in a dictionary with its correct segmentation, based on shape context descriptor, 2) segmenting th... View full abstract»

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  • Towards a SignWriting recognition system

    Publication Year: 2015, Page(s):26 - 30
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (804 KB) | HTML iconHTML

    SignWriting is a writing system for sign languages. It is based on visual symbols to represent the hand shapes, movements and facial expressions, among other elements. It has been adopted by more than 40 countries, but to ensure the social integration of the deaf community, writing systems based on sign languages should be properly incorporated into the Information Technology. This article reports... View full abstract»

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  • Combination of multiple aligned recognition outputs using WFST and LSTM

    Publication Year: 2015, Page(s):31 - 35
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (437 KB) | HTML iconHTML

    The contribution of this paper is a new strategy of integrating multiple recognition outputs of diverse recognizers. Such an integration can give higher performance and more accurate outputs than a single recognition system. The problem of aligning various Optical Character Recognition (OCR) results lies in the difficulties to find the correspondence on character, word, line, and page level. These... View full abstract»

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  • Class-adaptive zoning methods for recognizing handwritten digits and characters

    Publication Year: 2015, Page(s):36 - 40
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (445 KB) | HTML iconHTML

    This paper presents a new approach for zoning design based on a class-adaptive technique in which the optimal zoning method is defined for each class. For this purpose, in the zoning design stage, a multi-objective genetic algorithm was used to determine, for each class, both the optimal number of zones and the optimal zones for the Voronoi-based zoning method. The experimental tests were carried ... View full abstract»

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  • Keyword spotting in handwritten documents based on a generic text line HMM and a SVM verification

    Publication Year: 2015, Page(s):41 - 45
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (850 KB) | HTML iconHTML

    In this paper, we propose a novel system for keyword spotting in handwritten documents. Our approach proceeds in two steps: first a generic text line HMM provides a simple and flexible tool to localize the keyword and its character boundaries. In the second step, a SVM based verification system estimates and combines the character probabilities to provide keyword confidence scores which are furthe... View full abstract»

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  • Online handwritten Tibetan syllable recognition based on component segmentation method

    Publication Year: 2015, Page(s):46 - 50
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (737 KB) | HTML iconHTML

    Syllable-based input is more preferable than character-based input for Tibetan people due to the inherent characteristics of Tibetan characters. This paper presents a component segmentation-based recognition method for online handwritten Tibetan syllables. The input syllable is over-segmented into a sequence of sub-structure blocks (stroke blocks) with two-layer segmentation point annotation using... View full abstract»

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  • Arabic handwritten words off-line recognition based on HMMs and DBNs

    Publication Year: 2015, Page(s):51 - 55
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2106 KB) | HTML iconHTML

    In this work, we investigate the combination of PGM (Propabilistic Graphical Models) classifiers, either independent or coupled, for the recognition of Arabic handwritten words. The independent classifiers are vertical and horizontal HMMs (Hidden Markov Models) whose observable outputs are features extracted from the image columns and the image rows respectively. The coupled classifiers associate ... View full abstract»

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  • Binarizing complex scanned documents

    Publication Year: 2015, Page(s):56 - 60
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2747 KB) | HTML iconHTML

    Most binarization algorithms are suitable for scanned text documents and do not work adequately with complex documents that encompass photos, charts and text simultaneously. This paper presents a new binarization algorithm that works on complex documents. Each of the elements in the image is processed depending on its nature, thus their binarization takes that into account to preserve the original... View full abstract»

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  • Recognition confidence analysis of handwritten Chinese character with CNN

    Publication Year: 2015, Page(s):61 - 65
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1778 KB) | HTML iconHTML

    In this paper, we present an effective method to analyze the recognition confidence of handwritten Chinese character, based on the softmax regression score of a high performance convolutional neural network (CNN). Through careful and thorough statistics of 827,685 testing samples that randomly selected from total 8836 different classes of Chinese characters, we find that the confidence measurement... View full abstract»

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  • Multi-strategy tracking based text detection in scene videos

    Publication Year: 2015, Page(s):66 - 70
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1737 KB) | HTML iconHTML

    Text detection and tracking in scene videos are important prerequisites for content-based video analysis and retrieval, wearable camera systems and mobile devices augmented reality translators. Here, we present a novel multi-strategy tracking based text detection approach in scene videos. In this approach, a state-of-the-art scene text detection module [1] is first used to detect text in each vide... View full abstract»

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