Periodicity and Texel Size Estimation of Visual Texture Using Entropy Cues

Texture periodicity and texture element (texel) size are important characteristics for texture recognition and discrimination. In this paper, an approach to determine both, texture periodicity and texel size, is proposed. Our method is based on the entropy, a texture measure computed from the Sum and Difference Histograms. The entropy value is sensitive to the parameters in such histograms and takes its lowest value when the parameters match with texel size or its integer multiples, in any specific direction. We show the performance of our method by texture synthesis, tiling a sample of the detected size and measuring the similarity between the original image and the synthesized one, showing good results with regular textures and texels with different shapes, being useful for practical applications as well because of its simple implementation.

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Main Authors: Lizarraga Morales,Rocío, Sánchez Yáñez,Raúl E., Ayala Ramírez,Víctor
Format: Digital revista
Language:English
Published: Instituto Politécnico Nacional, Centro de Investigación en Computación 2011
Online Access:http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1405-55462011000100009
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spelling oai:scielo:S1405-554620110001000092012-02-01Periodicity and Texel Size Estimation of Visual Texture Using Entropy CuesLizarraga Morales,RocíoSánchez Yáñez,Raúl E.Ayala Ramírez,Víctor Image Processing Texture Size and Shape Texture Periodicity Entropy Texture periodicity and texture element (texel) size are important characteristics for texture recognition and discrimination. In this paper, an approach to determine both, texture periodicity and texel size, is proposed. Our method is based on the entropy, a texture measure computed from the Sum and Difference Histograms. The entropy value is sensitive to the parameters in such histograms and takes its lowest value when the parameters match with texel size or its integer multiples, in any specific direction. We show the performance of our method by texture synthesis, tiling a sample of the detected size and measuring the similarity between the original image and the synthesized one, showing good results with regular textures and texels with different shapes, being useful for practical applications as well because of its simple implementation.info:eu-repo/semantics/openAccessInstituto Politécnico Nacional, Centro de Investigación en ComputaciónComputación y Sistemas v.14 n.3 20112011-03-01info:eu-repo/semantics/articletext/htmlhttp://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1405-55462011000100009en
institution SCIELO
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country México
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region America del Norte
libraryname SciELO
language English
format Digital
author Lizarraga Morales,Rocío
Sánchez Yáñez,Raúl E.
Ayala Ramírez,Víctor
spellingShingle Lizarraga Morales,Rocío
Sánchez Yáñez,Raúl E.
Ayala Ramírez,Víctor
Periodicity and Texel Size Estimation of Visual Texture Using Entropy Cues
author_facet Lizarraga Morales,Rocío
Sánchez Yáñez,Raúl E.
Ayala Ramírez,Víctor
author_sort Lizarraga Morales,Rocío
title Periodicity and Texel Size Estimation of Visual Texture Using Entropy Cues
title_short Periodicity and Texel Size Estimation of Visual Texture Using Entropy Cues
title_full Periodicity and Texel Size Estimation of Visual Texture Using Entropy Cues
title_fullStr Periodicity and Texel Size Estimation of Visual Texture Using Entropy Cues
title_full_unstemmed Periodicity and Texel Size Estimation of Visual Texture Using Entropy Cues
title_sort periodicity and texel size estimation of visual texture using entropy cues
description Texture periodicity and texture element (texel) size are important characteristics for texture recognition and discrimination. In this paper, an approach to determine both, texture periodicity and texel size, is proposed. Our method is based on the entropy, a texture measure computed from the Sum and Difference Histograms. The entropy value is sensitive to the parameters in such histograms and takes its lowest value when the parameters match with texel size or its integer multiples, in any specific direction. We show the performance of our method by texture synthesis, tiling a sample of the detected size and measuring the similarity between the original image and the synthesized one, showing good results with regular textures and texels with different shapes, being useful for practical applications as well because of its simple implementation.
publisher Instituto Politécnico Nacional, Centro de Investigación en Computación
publishDate 2011
url http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1405-55462011000100009
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