Low-dimensional and comprehensive color texture description

Susana Alvarez, Anna Salvatella, Maria Vanrell, Xavier Otazu

Research output: Contribution to journalArticleResearchpeer-review

6 Citations (Scopus)

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. © 2011 Elsevier Inc. All rights reserved.
Original languageEnglish
Pages (from-to)54-67
JournalComputer Vision and Image Understanding
Volume116
DOIs
Publication statusPublished - 1 Jan 2012

Keywords

  • Basic terms vocabulary
  • Browsing
  • Color texture descriptors
  • Retrieval
  • Segmentation

Fingerprint Dive into the research topics of 'Low-dimensional and comprehensive color texture description'. Together they form a unique fingerprint.

Cite this