Weighted Zone based Kannada Character Recognition using Crack Feature Extraction Technique and Support Vector Machine Classification

ROOPANANDA M K

CALL FOR PAPERS : Feb-2026

Submission Last Date

25-Feb-26

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Weighted Zone based Kannada Character Recognition using Crack Feature Extraction Technique and Support Vector Machine Classification

Author(s):

ROOPANANDA M K , UBDT COLLEGE OF ENGINEERING

Keywords:

Crack Code, Support Vector Machine, Optical Character Recognition

Abstract:

Many methods and technologies evolved in recognizing optical character but very less research made on recognizing handwritten character because of the complexity of variations of individual way of writing style. Many systems are available for recognizing optical character. In this paper, I have worked recognizing the character using crack feature extraction and well-known SVM classifier but worked on new concept of WEIGHTED zone based. More weight need to be given on the zone which has maximum number of character overlapping on that zone thereby increasing the efficiency and maximum probability of finding a part of character.