Abstract
Handwriting is one of the behavioral biometric techniques for person identification. Our paper proposes a novel grapheme-based handwriting recognition system. First, the images of handwritings are segmented into graphemes and then graphemes are represented as projection profile. Then, dictionary is learnt from the images of handwriting using k-means clustering. Now using dictionary, writer feature vectors are generated and stored with writer label. Finally, query document features are matched with writer feature vectors using k-nearest neighbor. The outcome is the writer label with the highest similarity score.
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Pandey, P., Seeja, K.R. (2018). Forensic Writer Identification with Projection Profile Representation of Graphemes. In: Somani, A., Srivastava, S., Mundra, A., Rawat, S. (eds) Proceedings of First International Conference on Smart System, Innovations and Computing. Smart Innovation, Systems and Technologies, vol 79. Springer, Singapore. https://doi.org/10.1007/978-981-10-5828-8_13
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DOI: https://doi.org/10.1007/978-981-10-5828-8_13
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