Writer Identification Using Support Vector Machines and Texture Feature
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Abstract
A method is presented for text independent writer identification using multi-class SVM and texture feature of the whole script. 2D Gabor filter is applied to feature extraction, after that multi-class SVM is used to train and test the data. In the WS ICT writer script gallery collected from 87 persons, the proposed algorithm obtained competitive results.
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