An active contour model guided by LBP distributions

Authors:
Michalis A. Savelonas;Dimitris K. Iakovidis;Dimitris E. Maroulis;Stavros A. Karkanis
Affiliations:
Dept. of Informatics and Telecommunications, University of Athens, Athens, Greece;Dept. of Informatics and Telecommunications, University of Athens, Athens, Greece;Dept. of Informatics and Telecommunications, University of Athens, Athens, Greece;Dept. of Informatics and Computer Technology, Lamia Institute of Technology, Lamia, Greece
Venue:
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Year:
2006

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Abstract

The use of active contours for texture segmentation seems rather attractive in the recent research, indicating that such methodologies may provide more accurate results. In this paper, a novel model for texture segmentation is presented, combining advantages of the active contour approach with texture information acquired by the Local Binary Pattern (LBP) distribution. The proposed LBP scheme has been formulated in order to capture regional information extracted from distributions of LBP values, characterizing a neighborhood around each pixel, instead of using a single LBP value to characterize each pixel. The log-likelihood statistic is employed as a similarity measure between the LBP distributions, resulting to more detailed and accurate segmentation of texture images.