Library of visual descriptors and machine learning algorithms for texture and text detection
n. 27 (2019), Resumos
n. 27 (2019)

Library of visual descriptors and machine learning algorithms for texture and text detection

Resumos
https://doi.org/10.20396/revpibic2720192800
Publicado 2019-11-30
Jhonatas Conceição
Universidade Estadual de Campinas
Ricardo Torres
Universidade Estadual de Campinas
Allan Pinto
Universidade Estadual de Campinas
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Palavras-chave

Image classification
Text localization
Scene text detection

Como Citar

CONCEIÇÃO, Jhonatas; TORRES, Ricardo; PINTO, Allan. Library of visual descriptors and machine learning algorithms for texture and text detection. Revista dos Trabalhos de Iniciação Científica da UNICAMP, Campinas, SP, n. 27, p. 1–1, 2019. DOI: 10.20396/revpibic2720192800. Disponível em: https://econtents.bc.unicamp.br/eventos/index.php/pibic/article/view/2800. Acesso em: 20 abr. 2024.
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Resumo

In this article, we present the implementation of a solution for the text localization problem. More precisely, the solution presented in this article implements a prototype containing approaches for image characterization based on color and texture visual properties for supporting text region classification. As a result, we present a comparison study of several classifications systems for detecting text regions.

https://doi.org/10.20396/revpibic2720192800
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Referências

T. Ojala, M. Pietikainen, and T. Maenpaa, “Multiresolution gray-scale and rotation invariant texture classification with local binary patterns,” IEEE Trans. on Pattern Anal. Mach. Intell., vol. 24, no. 7, pp. 971–987, July 2002.
X. Wang, X. Ding, and C. Liu, “Gabor filters-based feature extraction for character recognition,” Pattern Recogn., vol. 38, no. 3, pp.369–379, Mar. 2005.
R. O. Stehling, M. A. Nascimento, and A. X. Falcão, “A compact and efficient image retrieval approach based on border/interior pixel classification,” in ACM 11th Intl. Conf. on Information and Knowledge Management, 2002, pp. 102–109.

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