Writer Identification Based on Local Contour Direction Features
Ding Hon · Video Engineering · 2013
A method based on local contour direction feature is proposed for off-line writer indentifaction in this paper. It reduces the inpact of stroke wideth by ignoring the fragments which do not directly connect the center point. The edge points are divided into 32 catigories to gain the directions of local fragments. This method counts the direction features in sliding windows and normalizes them into local contour direction features. The weighted Manhattan distance is used as similarity measurement at last. The experiments on ICDAR 2011 writer identification database with multi-languages show that the performances of the proposed method reach or exceed the state-of-art methods.