Describing reflectances for color segmentation robust to shadows, highlights, and textures

Eduard Vazquez, Ramon Baldrich, Joost Van De Weijer, Maria Vanrell

Research output: Contribution to journalArticleResearchpeer-review

29 Citations (Scopus)

Abstract

The segmentation of a single material reflectance is a challenging problem due to the considerable variation in image measurements caused by the geometry of the object, shadows, and specularities. The combination of these effects has been modeled by the dichromatic reflection model. However, the application of the model to real-world images is limited due to unknown acquisition parameters and compression artifacts. In this paper, we present a robust model for the shape of a single material reflectance in histogram space. The method is based on a multilocal creaseness analysis of the histogram which results in a set of ridges representing the material reflectances. The segmentation method derived from these ridges is robust to both shadow, shading and specularities, and texture in real-world images. We further complete the method by incorporating prior knowledge from image statistics, and incorporate spatial coherence by using multiscale color contrast information. Results obtained show that our method clearly outperforms state-of-the-art segmentation methods on a widely used segmentation benchmark, having as a main characteristic its excellent performance in the presence of shadows and highlights at low computational cost. © 2006 IEEE.
Original languageEnglish
Article number5551152
Pages (from-to)917-930
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume33
Issue number5
DOIs
Publication statusPublished - 14 Feb 2011

Keywords

  • color
  • Segmentation

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