Offline Text-Independent Chinese Writer Identification Using GLDM Features

This paper presents a method using retrieval mechanism along with Gray-Level Difference Method (GLDM) feature extraction, an approach based on the textural features which is firstly introduced for off-line, text-independent Chinese writer identification. A widely used performance evaluation database HIT-MW has been used for conducting the experiment. An improvement in the identification rates has been revealed in the experimental evaluations by decreasing the search space using a writer retrieval mechanism prior to identification.

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