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Entropy-Based Localization of Textured Regions

  • Liliana Lo Presti
  • Marco La Cascia
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6978)

Abstract

Appearance description is a relevant field in computer vision that enables object recognition in domains as re-identification, retrieval and classification. Important cues to describe appearance are colors and textures. However, in real cases, texture detection is challenging due to occlusions and to deformations of the clothing while person’s pose changes. Moreover, in some cases, the processed images have a low resolution and methods at the state of the art for texture analysis are not appropriate.

In this paper, we deal with the problem of localizing real textures for clothing description purposes, such as stripes and/or complex patterns. Our method uses the entropy of primitive distribution to measure if a texture is present in a region and applies a quad-tree method for texture segmentation.

We performed experiments on a publicly available dataset and compared to a method at the state of the art[16]. Our experiments showed our method has satisfactory performance.

Keywords

Local Binary Pattern Latent Dirichlet Allocation Texture Region Texture Segmentation Texture Area 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Liliana Lo Presti
    • 1
  • Marco La Cascia
    • 1
  1. 1.University of PalermoItaly

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