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- W187397233 abstract "Recognizing the writer of a handwritten document has been an active research area over the last few years and is at the heart of many applications in biometrics, forensics and historical document analysis. In this paper, we present a novel approach for text-independent writer recognition from Arabic handwritten documents. To characterize the handwriting styles of different writers involved in the evaluation of our approach, we have used two texture methods based on edge hinge features and run-lengths features. The efficiency of the proposed approach is demonstrated experimentally by the classification of 1375 handwritten documents collected from 275 different Arabic writers." @default.
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- W187397233 date "2012-01-01" @default.
- W187397233 modified "2023-10-14" @default.
- W187397233 title "Writer Recognition on Arabic Handwritten Documents" @default.
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- W187397233 doi "https://doi.org/10.1007/978-3-642-31254-0_56" @default.
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