Two-Pass Segmentation for Marathi Character Extraction

Madhav A. Kankhar*, C. Namrata Mahender **
*-** Department of Computer Science & Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India.
Periodicity:July - December'2020
DOI : https://doi.org/10.26634/jpr.7.2.18148

Abstract

Handwriting recognition is very complex but a much needed system for various purposes. Work on English language can be seen in full swing as compared to Indian languages. Free style handwriting has various challenges due to the individual variation in writing style, along with half characters, joint characters, overlapped characters, etc. are major when considering written in Devanagari script. Computational studies of Indian languages written using Devanagari script, including Marathi, are in its primary stage. The present work focuses on proper character segmentation in Marathi words for better post-processing and recognition rate as segmentation is an important stage that affects post-processing performance. Data is collected from native speakers of the Marathi language, with 3000 samples handwritten words in Marathi language for numbers from one to ten, and this paper discusses the proposed two-pass segmentation approach to extract written Marathi script.

Keywords

Online Recognition, Offline Recognition, Segmentation, Handwriting Recognition, Preprocessing.

How to Cite this Article?

Kankhar, M. A., and Mahender, C. N. (2020). Two-Pass Segmentation for Marathi Character Extraction. i-manager's Journal on Pattern Recognition, 7(2), 1-6. https://doi.org/10.26634/jpr.7.2.18148

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