Shape and data-driven texture segmentation using local binary patterns

Tekeli, Erkin and Çetin, Müjdat and Erçil, Aytül (2007) Shape and data-driven texture segmentation using local binary patterns. In: EURASIP European Signal Processing Conference, Poznan, Poland

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We propose a shape and data driven texture segmentation method using local binary patterns (LBP) and active contours. In particular, we pass textured images through a new LBP-based filter, which produces non-textured images. In this “filtered” domain each textured region of the original image exhibits a characteristic intensity distribution. In this domain we pose the segmentation problem as an optimization problem in a Bayesian framework. The cost functional contains a data-driven term, as well as a term that brings in information about the shapes of the objects to be segmented. We solve the optimization problem using level set-based active contours. Our experimental results on synthetic and real textures demonstrate the effectiveness of our approach in segmenting challenging textures as well as its robustness to missing data and occlusions.

Item Type:Papers in Conference Proceedings
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
ID Code:6568
Deposited By:Müjdat Çetin
Deposited On:30 Oct 2007 01:00
Last Modified:30 Oct 2007 01:00

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