Eigen Combination of Colour and Texture Informations for Image Segmentation

  • D. Attia
  • C. Meurie
  • Y. Ruichek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7340)


In this paper, we present a new combination of colour and texture informations for image segmentation. This technique is based on principal components analysis of a 3D points cloud, followed by an eigenvalues analysis. A set of colour gradients (morphological, Di-Zenzo) and texture gradients (Gabor, three Haralick attributes, Alternative Sequential Filter (ASF)) are used to test the proposed combination. The segmentation is performed using a hybrid gradient based watershed algorithm. The major contribution of this work consists in combining locally colour and texture informations using an adaptive and non parametric approach. The proposed method is tested on 100 images from the Berkley dataset [1] and evaluated with the Mean Square Error (MSE), the Variation of Information (VI) and the Probabilistic Rand Index (PRI).


Mean Square Error Image Segmentation Segmentation Result Texture Information Eigenvalue Analysis 
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 2012

Authors and Affiliations

  • D. Attia
    • 1
  • C. Meurie
    • 1
  • Y. Ruichek
    • 1
  1. 1.Institut Régional Supérieur du Travail Educatif et Social de Bourgogne, Laboratoire Systémes et TransportsUniversité de Technologie de Belfort-MontbéliardBelfort CedexFrance

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