Unconstrained Handwritten Text Line Segmentation for Kannada Language
Shakunthala B. S1, C S Pillai2

1Shakunthala B S*, Assistant Professor, Department of Information Science & Engineering, Kalpataru Institute of Technology, Tiptur, Karnataka, India.
2Dr. C S Pillai, Professor, Department of Computer Science & Engineering, ACS college of engineering, Bangalore, Karnataka, India.

Manuscript received on September 15, 2019. | Revised Manuscript received on 22 September, 2019. | Manuscript published on October 10, 2019. | PP: 953-956 | Volume-8 Issue-12, October 2019. | Retrieval Number: J962408810199/2019©BEIESP | DOI: 10.35940/ijitee.J9624.1081219
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Abstract: Segmentation is division of something into smaller parts and one of the Component of character recognition system. Separation of characters, words and lines are done in Segmentation from text documents. character recognition is a process which allows computers to recognize written or printed characters such as numbers or letters and to change them into a form that the computer can use. the accuracy of OCR system is done by taking the output of an OCR run for an image and comparing it to the original version of the same text. The main aim of this paper is to find out the various text line segmentations are Projection profiles, Weighted Bucket Method. Proposed method is horizontal projection profile and connected component method on Handwritten Kannada language. These methods are used for experimentation and finally comparing their accuracy and results.
Keywords: Projection Profiles, Weighted Bucket Method. Horizontal Projection Profile and Connected Component Method, Segmentation, Preprocessing
Scope of the Article: Component-Based Software Engineering