No abstract

In this paper, we present a new image segmentation algorithm which is based on local binary patterns (LBPs) and the combinatorial pyramid and which preserves structural correctness and image topology. For this purpose, we define a codification of LBPs using graph pyramids. Since the LBP code characterizes the topological category (local max, min, slope, saddle) of the gray level landscape around the center region, we use it to obtain a "minimal" image representation in terms of the topological characterization of a given 2D grayscale image. Based on this idea, we further describe our hierarchical texture aware image segmentation algorithm and compare its segmentation output and the "minimal" image representation. KeywordsLocal binary patterns • Irregular graph pyramid • Primal and dual graph • Topological characterization • Image segmentation Author was partially supported by IMUS and Spanish Ministry under grant MTM2015-67072-P (MINECO/FEDER, UE).

Abstract. In this paper, a new codification of Local Binary Patterns (LBP) is given using graph pyramids. The LBP code characterizes the topological category (local max, min, slope, saddle) of the gray level landscape around the center region. Given a 2D grayscale image I, our goal is to obtain a simplified image which can be seen as "minimal" representation in terms of topological characterization of I. For this, a method is developed based on merging regions and Minimum Contrast Algorithm.

No abstract