Offline Character Recognition of Handwritten MODI Script Using Wavelet Transform and Decision Tree Classifier
Decision tree classifier; Handwritten character recognition; MODI script; Pattern recognition; Wavelet transform
MODI script is derived from the N?gari family of scripts, and it was used for writing Marathi until twentieth century. Though currently not used as an official script, it has historical importance, as a large volume of manuscripts are preserved at various libraries across India. With the use of an appropriate recognition system, the handwritten documents can be transferred into digital media, so that it can be conveniently viewed, edited, or transliterated to other scripts. The research on MODI script is still in the initial stages, and there is a considerable demand for more research in this field. An implementation of wavelet transform-based feature extraction for MODI scripts character recognition is discussed in this paper. The experiment is performed using Daubechies, Haar, and Symlet wavelets, and performance comparison between these different mother wavelets is carried out. Decision tree classifier is used for the classification process, and the results indicate that the feature extraction using Daubechies wavelet yielded better character recognition result. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes in Networks and Systems, Vol-191, pp. 509-517.
Springer Science and Business Media Deutschland GmbH
Joseph S., CHRIST (Deemed to be University), Bengaluru, India, Carmel College of Arts, Science and Commerce for Women, Goa, India; George J.P., CHRIST (Deemed to be University), Bengaluru, India