Abstract
In this paper a new method of classification is proposed by making hybrid models by using 3 different technique. One of them is correlation method, which use statistical template matching technique. Other one is principal component analysis in which for each image (character) there are some principal component, named Eigen value, and Eigen vectors. Third is Hough line detection technique, with the help of this we can find number of line segments in a character. Here with the experiments we can say that with the help of mixture of two or more different methods we can get better result. In this paper, we have implemented above techniques without using previous database of character images and getting 94.8% accuracy.
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Hotwani, K., Agarwal, S., Paswan, R. (2018). Hybrid Models for Offline Handwritten Character Recognition System Without Using any Prior Database Images. In: Satapathy, S., Bhateja, V., Raju, K., Janakiramaiah, B. (eds) Data Engineering and Intelligent Computing. Advances in Intelligent Systems and Computing, vol 542 . Springer, Singapore. https://doi.org/10.1007/978-981-10-3223-3_10
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DOI: https://doi.org/10.1007/978-981-10-3223-3_10
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