Writer recognition by using new searching algorithm in new local arc method
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Text-independent writer recognition using multi-script handwritten texts
Pattern Recognition Letters
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In the previous studies, authors proposed a new local arc method with new similarity evaluation function to the off-line writer recognition, and obtained high recognition ratios. However, the calculated similarity values are comparatively close each other. Therefore, it is very difficult to improve the accuracy any more. In this study, it is assumed that the amount of the characteristic features appeared to the curvature distribution may be different as the difference of the character size. Then, similarity values of five character sizes were compared, and the optimum character size for the new local arc method was examined. As a result, it turned out that the similarity values are greatly influenced by the character size, and the best character size and arc chord length are obtained for the writer recognition by the new local arc method.