Writer identification with n ‐tuple direction feature from contour
Ali Reza Ghanbarian, Golnaz Ghiasi, Reza Safabakhsh, Narges Arastouie · IET Image Processing · 2019
This study introduces an effective solution for text‐independent writer identification by generalising contour‐hinge feature, which is called n ‐tuple direction feature. For extracting n ‐tuple direction feature, the authors first obtain all contours from connected components, then n + 1 points are considered on the contour with a certain distance apart, and next, the directions of the fragments connecting two successive points are computed. The n + 1 points move on the contour and the n ‐dimensional histogram of directions is computed. The proposed method is evaluated on large Farsi and English databases. A correct writer identification rate of 92.2% for English handwritings from 900 persons and 97.7% for Farsi handwritings from 600 persons are achieved. Comparison between the proposed method and other studies shows the promising performance and superiority of the proposed method.