Eigen combination of colour and texture informations for image segmentation

Authors:
D. Attia;C. Meurie;Y. Ruichek
Affiliations:
Institut Régional Supérieur du Travail Educatif et Social de Bourgogne, Laboratoire Systémes et Transports, Université de Technologie de Belfort-Montbéliard, Belfort Cedex ...;Institut Régional Supérieur du Travail Educatif et Social de Bourgogne, Laboratoire Systémes et Transports, Université de Technologie de Belfort-Montbéliard, Belfort Cedex ...;Institut Régional Supérieur du Travail Educatif et Social de Bourgogne, Laboratoire Systémes et Transports, Université de Technologie de Belfort-Montbéliard, Belfort Cedex ...
Venue:
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
Year:
2012

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Abstract

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).