A Combined Approach of Feature Selection and Machine Learning Technique for Handwritten Character Recognition

6 Pages Posted: 24 Jun 2019

See all articles by Saptadeepa Kalita

Saptadeepa Kalita

Sharda University - Department of Computer Science

Diwakar Gautam

Sharda University - Department of Computer Science

Ashok Kumar Sahoo

Sharda University - Department of Computer Science

Rajiv Kumar

Sharda University

Date Written: June 24, 2019

Abstract

Handwritten Character Recognition has proven its worth in most challenging research areas in the various application based domains like bank cheques, signature verification, aids for blind persons, etc. The role of alphabetical characters is quite focused to recognize the scanned text that can be further deployed for sentimental analysis. In this research paper, we have deployed a promising approach to recognize handwritten English alphabets. We have mainly aimed in the digits recognition. The features of Handwritten Numerals are extracted using geometrical and gradient-based measures. The redundancy of feature set is reduced using feature selection method, and machine learning approach is deployed to generalize the decision boundary. The experimental outcome proves its promising worth comparable to existing arts.

Keywords: geometrical features, gradient feature, selection, cross-validation decision, boundary

Suggested Citation

Kalita, Saptadeepa and Gautam, Diwakar and Kumar Sahoo, Ashok and Kumar, Rajiv, A Combined Approach of Feature Selection and Machine Learning Technique for Handwritten Character Recognition (June 24, 2019). International Journal of Advanced Studies of Scientific Research, Vol. 4, No. 4, 2019, Available at SSRN: https://ssrn.com/abstract=3408997

Saptadeepa Kalita (Contact Author)

Sharda University - Department of Computer Science ( email )

Gr. Noida, 201306
India

Diwakar Gautam

Sharda University - Department of Computer Science ( email )

Gr. Noida, 201306
India

Ashok Kumar Sahoo

Sharda University - Department of Computer Science ( email )

Gr. Noida, 201306
India

Rajiv Kumar

Sharda University ( email )

Knowledge Park III
Greater Noida
Greater Noida, Uttar Pradesg 201301
India

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