LBP and Irregular Graph Pyramids Martin Cerman , Rocio Gonzalez-Diaz , and Walter Kropatsch 1 PRIP Group, Vienna University of Technology, 1040 Wien, Austria mcerman@prip.tuwien.ac.at, rogodi@us.es 2 Applied Mathematics Department, School of Computer Engineering, University of Seville, Seville, Spain krw@prip.tuwien.ac.at 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. Keywords: Local binary patterns · Irregular graph pyramid · Primal and dual graph · Topological characterization · Minimum contrast algo- rithm 1 Introduction Given a grayscale digital image I , the Local Binary Pattern LBP (I )[12, 13] is a grayscale digital image used to represent the texture element at each pixel in I . This is currently the most frequently used texture descriptor [18] with outstanding results in applications ranging from segmentation and classification [15], object detection [11] to gender classification [16]. Typically the LBP opera- tor is applied to all 3 × 3 image windows of the considered texture (region). Then the histogram provides the characteristic features of the texture. After training the feature space with the textures of interest new textures can be classified with very good discrimination. While the LBP code of a 3 × 3 window needs 8 bits for a single code, larger windows need more bits or even a varying number of bits if a multiresolution approach is chosen. The new encoding overcomes this drawback by transferring the code from the pixels to the neighbor relations (edges of the neighborhood M. Cerman—Acknowledges the support of the PRIP Club, the organization of friends and promoters of Pattern Recognition and Image Processing activities, Vienna, Austria. R. Gonzalez-Diaz—Author partially supported by IMUS, Spanish Ministry under grant MTM2012-32706 and ESF ACAT program. c