Abstract
This paper presents a recognition system for isolated handwritten Bangla words, with a fixed lexicon, using a Hidden Markov Model (HMM). A stochastic search method, namely, Genetic Algorithm (GA) is used to train the HMM. The HMM is a left-right HMM. For feature extraction, the image boundary is traced both in the anticlockwise and clockwise directions and the significant changes in direction along the boundary are noted. Certain features defined on the basis of these changes are used in the proposed model.
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Bhowmik, T.K., Parui, S.K., Kar, M., Roy, U. (2007). HMM Parameter Estimation with Genetic Algorithm for Handwritten Word Recognition. In: Ghosh, A., De, R.K., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2007. Lecture Notes in Computer Science, vol 4815. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77046-6_66
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DOI: https://doi.org/10.1007/978-3-540-77046-6_66
Publisher Name: Springer, Berlin, Heidelberg
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