Abstract
In this work, we present a new protocol for a novel biometric scenario that is called writer retrieval. Precisely, we propose to use the Histogram Of Templates (HOT) to generate features from handwritten text images. Then, the retrieval task is achieved by SVM classifier trained according to a writer independent strategy. Experiments are conducted on the CVL database which contains 310 writers (1604 documents written in English and German). The results obtained in terms of overall accuracy highlight the effectiveness of the proposed system.
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Bouibed, M.L., Nemmour, H., Chibani, Y. (2019). Writer Retrieval Using Histogram Of Templates Features and SVM. In: Chadli, M., Bououden, S., Ziani, S., Zelinka, I. (eds) Advanced Control Engineering Methods in Electrical Engineering Systems. ICEECA 2017. Lecture Notes in Electrical Engineering, vol 522. Springer, Cham. https://doi.org/10.1007/978-3-319-97816-1_41
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DOI: https://doi.org/10.1007/978-3-319-97816-1_41
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