Writer Identification for Handwritten Telugu Documents Using Directional Morphological Features

Abstract

Linking a person based on handwritten documents is one of the oldest techniques that is used by crime investigators and forensic scientists. The importance of writer recognition in anthrax letter cases has made this examination popular in recent years. In this paper we propose four feature set namely directional opening, directional closing, direction erosion and k-curvature features for writer recognition on Telugu handwritten documents. Each of the features is extracted from the words after dividing them into a number of cells and then subjected to a nearest neighbor classifier for writer recognition. Although the results of each of the feature set is quite encouraging, the directional opening feature outperforms other feature sets.