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Performance Evaluation of Symbol Recognition

Identifieur interne : 001B99 ( Istex/Corpus ); précédent : 001B98; suivant : 001C00

Performance Evaluation of Symbol Recognition

Auteurs : Ernest Valveny ; Philippe Dosch

Source :

RBID : ISTEX:0B858C7754E8CA8F0C80ABA7D970CD7DBF8DB666

Abstract

Abstract: Symbol recognition is one of the central problems in the field of graphics recognition. Many methods and approaches have been developed in the context of several application domains. In the last years, the need for generic methods, able to perform well on large sets of symbols in different domains, has become clear. Thus, standard evaluation datasets and protocols have to be built up in order to be able to evaluate the performance of all these methods. In this paper we discuss several points which should be taken into account in the design of such evaluation framework, raising a number of open questions for further discussion. These issues were the starting point of the organization of the contest on symbol recognition held during the last Workshop on Graphics Recognition (GREC’03). We also summarize the main features of the dataset and the protocol of evaluation used in the contest, as a first step to define a general evaluation framework, giving answer to these open questions.

Url:
DOI: 10.1007/978-3-540-28640-0_34

Links to Exploration step

ISTEX:0B858C7754E8CA8F0C80ABA7D970CD7DBF8DB666

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<Para>Symbol recognition is one of the central problems in the field of graphics recognition. Many methods and approaches have been developed in the context of several application domains. In the last years, the need for generic methods, able to perform well on large sets of symbols in different domains, has become clear. Thus, standard evaluation datasets and protocols have to be built up in order to be able to evaluate the performance of all these methods. In this paper we discuss several points which should be taken into account in the design of such evaluation framework, raising a number of open questions for further discussion. These issues were the starting point of the organization of the contest on symbol recognition held during the last Workshop on Graphics Recognition (GREC’03). We also summarize the main features of the dataset and the protocol of evaluation used in the contest, as a first step to define a general evaluation framework, giving answer to these open questions.</Para>
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