Ninth International Workshop on Frontiers in Handwriting Recognition

26-29 Oct. 2004

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  • Proceedings. Ninth International Workshop on Frontiers in Handwriting Recognition

    Publication Year: 2004
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  • Ninth International Workshop on Frontiers in Handwriting Recognition - Title Page

    Publication Year: 2004, Page(s):i - iii
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  • Ninth International Workshop on Frontiers in Handwriting Recognition - Copyright Page

    Publication Year: 2004, Page(s): iv
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  • Ninth International Workshop on Frontiers in Handwriting Recognition - Table of contents

    Publication Year: 2004, Page(s):v - xii
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  • Foreword

    Publication Year: 2004, Page(s): xiii
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  • Organizing Committee

    Publication Year: 2004, Page(s): xiv
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  • Program Committee

    Publication Year: 2004, Page(s): xv
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  • Reviewers

    Publication Year: 2004, Page(s): xvi
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  • Sponsors

    Publication Year: 2004, Page(s): xvii
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  • Online character recognition using eigen-deformations

    Publication Year: 2004, Page(s):3 - 8
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (432 KB) | HTML iconHTML

    In online character recognition based on elastic matching, such as dynamic programming matching, many of misrecognitions are often caused by overfitting, which is the phenomenon that the distance between reference pattern of an incorrect category and an input pattern is underestimated by unnatural matching. In this paper, a new recognition technique is proposed where category-specific deformations... View full abstract»

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  • Self-supervised adaptation for on-line text recognition

    Publication Year: 2004, Page(s):9 - 13
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (160 KB) | HTML iconHTML

    We developed a handwritten text recognizer for on-line text written on a touch-terminal. This system is based on the activation-verification cognitive model. It is composed of three experts dedicated respectively to signal segmentation in symbols, symbol classification and lexical analysis of the classification results. The baseline system is writer-independent. We present in this paper several st... View full abstract»

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  • Handling spatial information in on-line handwriting recognition

    Publication Year: 2004, Page(s):14 - 19
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (152 KB) | HTML iconHTML

    This paper focuses on handling the two-dimensional feature of on-line handwriting signals in recognition engines. This spatial information is taken into account in various ways depending on the nature of characters to be recognized. We review some techniques used in the literature and investigate new ones to represent and model the spatial information in handwriting recognition engines. We compare... View full abstract»

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  • Generative models and Bayesian model comparison for shape recognition

    Publication Year: 2004, Page(s):20 - 25
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (152 KB) | HTML iconHTML

    Recognition of hand-drawn shapes is an important and widely studied problem. By adopting a generative probabilistic framework we are able to formulate a robust and flexible approach to shape recognition which allows for a wide range of shapes and which can recognize new shapes from a single exemplar. It also provides meaningful probabilistic measures of model score, which can be used as part of a ... View full abstract»

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  • Modulating population granularity for improved diagnosis of developmental dyspraxia from dynamic drawing analysis

    Publication Year: 2004, Page(s):26 - 31
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (216 KB) | HTML iconHTML

    In this paper, we describe a diagnostic tool for automated assessment of developmental dyspraxia among children using Beery's VMI test drawings. Various attributes extracted from the dynamic pen movements are used for this assessment. The test environment is exactly the same as that used in conventional VMI tests, except that the test population is partitioned into several age-bands. The populatio... View full abstract»

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  • Contextual recognition of hand-drawn diagrams with conditional random fields

    Publication Year: 2004, Page(s):32 - 37
    Cited by:  Papers (13)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (216 KB) | HTML iconHTML

    Hand-drawn diagrams present a complex recognition problem. Fragments of the drawing are often individually ambiguous, and require context to be interpreted. We present a recognizer based on conditional random fields (CRFs) that jointly analyze all drawing fragments in order to incorporate contextual cues. The classification of each fragment influences the classification of its neighbors. CRFs allo... View full abstract»

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  • Support vector machines for handwritten numerical string recognition

    Publication Year: 2004, Page(s):39 - 44
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (192 KB) | HTML iconHTML

    In this paper we discuss the use of SVMs to recognize handwritten numerical strings. Such a problem is more complex than recognizing isolated digits since one must deal with problems such as segmentation, overlapping, unknown number of digits, etc. In order to perform our experiments, we have used a segmentation-based recognition system using heuristic over-segmentation. The contribution of this p... View full abstract»

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  • A classifier based on distance between test samples and average patterns of categorical nearest neighbors

    Publication Year: 2004, Page(s):45 - 50
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (480 KB) | HTML iconHTML

    The recognition rate of the typical nonparametric method "k-nearest neighbor rule (kNN)" is degraded when the dimensionality of feature vectors is large. Another nonparametric method "linear subspace methods" cannot represent the local distribution of patterns, so recognition rates decrease when pattern distribution is not normal distribution. This paper presents a classifier that outputs the clas... View full abstract»

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  • Classification of time-series data using a generative/discriminative hybrid

    Publication Year: 2004, Page(s):51 - 56
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (136 KB) | HTML iconHTML

    Classification of time-series data using discriminative models such as SVMs is very hard due to the variable length of this type of data. On the other hand generative models such as HMMs have become the standard tool for modeling time-series data due to their efficiency. This paper proposes a general generative/discriminative hybrid that uses HMMs to map the variable length time-series data into a... View full abstract»

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  • Speeding up the decision making of support vector classifiers

    Publication Year: 2004, Page(s):57 - 62
    Cited by:  Papers (2)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (664 KB) | HTML iconHTML

    In this paper, we propose a new approach for speeding up the decision making of support vector classifiers (SVC) in the context of multi-class classification. A two-stage system embedded within a probabilistic framework is presented. In the first stage we pre-estimate the posterior probabilities with a model-based approach and we re-estimate only the highest probabilities with appropriate SVCs in ... View full abstract»

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  • Combination of three classifiers with different architectures for handwritten word recognition

    Publication Year: 2004, Page(s):63 - 68
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (152 KB) | HTML iconHTML

    The study of multiple classifier systems has become an area of intensive research in pattern recognition recently. Also in handwriting recognition, systems combining several classifiers have been investigated. In this paper the combination of three classifiers for handwritten word recognition with different architectures is studied. In addition a new ensemble method working with several base class... View full abstract»

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  • Normalization ensemble for handwritten character recognition

    Publication Year: 2004, Page(s):69 - 74
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (240 KB) | HTML iconHTML

    This paper proposes a multiple classifier approach, called normalization ensemble, for handwritten character recognition by combining multiple normalization methods. By varying the coordinate mapping mode, we have devised 14 normalization functions, and switching on/off slant correction results in 28 instantiated classifiers. We would show that the classifiers with different normalization methods ... View full abstract»

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  • Boosting driven by error free regions

    Publication Year: 2004, Page(s):75 - 80
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (160 KB) | HTML iconHTML

    Multiple classifier systems improve the recognition performance of a discrimination task considerably, which makes them very attractive for pattern recognition products. Two aspects are eminently important: firstly, how can a powerful classifier ensemble be generated effectively and secondly, what classifier combination rule would produce the best collective result. This paper proposes a new boost... View full abstract»

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  • Unsupervised feature selection for ensemble of classifiers

    Publication Year: 2004, Page(s):81 - 86
    Cited by:  Papers (1)  |  Patents (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (152 KB) | HTML iconHTML

    In this paper we discuss a strategy to create ensemble of classifiers based on unsupervised features selection. It takes into account a hierarchical multi-objective genetic algorithm that generates a set of classifiers by performing feature selection and then combines them to provide a set of powerful ensembles. The proposed method is evaluated in the context of handwritten month word recognition,... View full abstract»

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  • Using informational confidence values for classifier combination: an experiment with combined on-line/off-line Japanese character recognition

    Publication Year: 2004, Page(s):87 - 92
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (216 KB) | HTML iconHTML

    Classifier combination has turned out to be a powerful tool for achieving high recognition rates, especially in fields where the development of a powerful single classifier system requires considerable efforts. However, the intensive investigation of multiple classifier systems has not resulted in a convincing theoretical foundation yet. Lacking proper mathematical concepts, many systems still use... View full abstract»

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  • A syntax-directed method for numerical field extraction using classifier combination

    Publication Year: 2004, Page(s):93 - 98
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (288 KB) | HTML iconHTML

    In this article, we propose a method for the automatic extraction of numerical fields in handwritten documents. The method exploits the syntax of a numerical field as an a priori knowledge to extract the connected component sequences from the document. For that, we have to label the connected components as "belonging to a numerical field" or not. We propose a method for discriminating the connecte... View full abstract»

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