Skeleton Hinge Distribution for Writer Identification
2016
In this paper, a feature that is based on statistical directional features is presented. Specifically, an improvement of the statistical feature: edge hinge distribution, is attempted. Furthermore, different matching techniques are applied. For the evaluation, the Firemaker DB was used, which consists of samples from 250 writers, including 4 pages per writer. The suggested feature, the skeleton hinge distribution, achieved accuracy of 90.8% using nearest neighbor with Manhattan distance for matching.
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