Writer identification using edge based features

Abstract

In this paper we present a new method for writer identification, which extract original Local Binary Pattern(LBP) of different radius and Edge descriptors from the edge points of the handwriting. Then, we make combinations of these edge based features. Experimental results demonstrate that the combination of edge points based features outperform traditional features extracted from the whole text, which can get state-of-the-art performance on CVL andICDAR2013 datasets.