Low-dimensional and comprehensive color texture description

  • Authors:
  • Susana Alvarez;Anna Salvatella;Maria Vanrell;Xavier Otazu

  • Affiliations:
  • Dept. Enginyeria Informítica i Matemítiques, Universitat Rovira i Virgili, Campus Sescelades, Avinguda dels Països Catalans, 26, 43007 Tarragona, Spain;Computer Vision Center, Edifici O, Campus UAB, 08193 Bellaterra, Barcelona, Spain;Dept. Ciències de la Computació, Universitat Autònoma de Barcelona, Spain and Computer Vision Center, Edifici O, Campus UAB, 08193 Bellaterra, Barcelona, Spain;Dept. Ciències de la Computació, Universitat Autònoma de Barcelona, Spain and Computer Vision Center, Edifici O, Campus UAB, 08193 Bellaterra, Barcelona, Spain

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2012

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Abstract

Image retrieval can be dealt by combining standard descriptors, such as those of MPEG-7, which are defined independently for each visual cue (e.g. SCD or CLD for Color, HTD for texture or EHD for edges). A common problem is to combine similarities coming from descriptors representing different concepts in different spaces. In this paper we propose a color texture description that bypasses this problem from its inherent definition. It is based on a low dimensional space with 6 perceptual axes. Texture is described in a 3D space derived from a direct implementation of the original Julesz's Texton theory and color is described in a 3D perceptual space. This early fusion through the blob concept in these two bounded spaces avoids the problem and allows us to derive a sparse color-texture descriptor that achieves similar performance compared to MPEG-7 in image retrieval. Moreover, our descriptor presents comprehensive qualities since it can also be applied either in segmentation or browsing: (a) a dense image representation is defined from the descriptor showing a reasonable performance in locating texture patterns included in complex images; and (b) a vocabulary of basic terms is derived to build an intermediate level descriptor in natural language improving browsing by bridging semantic gap.