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Ninth International Workshop on Frontiers in Handwriting Recognition (2004)
Kokubunji, Tokyo, Japan
Oct. 26, 2004 to Oct. 29, 2004
ISSN: 1550-5235
ISBN: 0-7695-2187-8
pp: 185-190
Lambert Schomaker , AI Institute
Marius Bulacu , AI Institute
Katrin Franke , AI Institute
In this paper, a method for off-line writer identification is presented, using the contours of fragmented connected-components in mixed-style handwritten samples of limited size. The writer is considered to be characterized by a stochastic pattern generator, producing a family of character fragments (fraglets). Using a codebook of such fraglets from an independent training set, the probability distribution of fraglet contours was computed for an independent test set. Results revealed a high sensitivity of the fraglet histogram in identifying individual writers on the basis of a paragraph of text. Large-scale experiments on the optimal size of Kohonen maps of fraglet contours were performed, showing usable classification rates within a non-critical range of Kohonen map dimensions. Further validation experiments on variable-sized random subsets from an independent set of 215 writers gives additional support for the proposed method. The proposed automatic approach bridges the gap between image-statistics approaches and manual character-based methods.
Lambert Schomaker, Marius Bulacu, Katrin Franke, "Automatic Writer Identification Using Fragmented Connected-Component Contours", Ninth International Workshop on Frontiers in Handwriting Recognition, vol. 00, no. , pp. 185-190, 2004, doi:10.1109/IWFHR.2004.22
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