A Local binary patterns and shape priors based texture segmentation method

Tekeli, Erkin and Çetin, Müjdat and Erçil, Aytül (2007) A Local binary patterns and shape priors based texture segmentation method. In: IEEE Conference on Signal Processing and Communications Applications, Eskişehir, Turkey

[thumbnail of tekeli_SIU07.pdf] PDF
tekeli_SIU07.pdf

Download (1MB)

Abstract

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
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Müjdat Çetin
Date Deposited: 29 Oct 2007 19:11
Last Modified: 26 Apr 2022 08:43
URI: https://research.sabanciuniv.edu/id/eprint/6541

Actions (login required)

View Item
View Item