research-article

Using moments features from Gabor directional images for Kannada handwriting character recognition

Authors:

M. SasikumarAuthors Info & Claims

ICWET '10: Proceedings of the International Conference and Workshop on Emerging Trends in Technology

Pages 53 - 58

https://doi.org/10.1145/1741906.1741916

Published: 26 February 2010 Publication History

Abstract

Handwriting character recognition (HCR) for Indian Languages is an important problem where there is relatively little work has been done. In this paper, we investigate the moments features on Kannada handwritten basic character set of 49 letters. Moments features are extracted from the preprocessed original images by most of the researchers. Kannada characters are curved in nature with some symmetry observed in the shape. This information can be best extracted as a feature if we extract moment features from the directional images. So we are finding 4 directional images using Gabor wavelets from the dynamically preprocessed original images. We then extract moments features from them. The comparison of moments features of 4 directional images with original images when tested on Multi Layer Perceptron with Back Propagation Neural Network shows an average improvement of 13% from 72% to 85%. The mean performance of the system with these two features together is 92%.

References

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Ragha Leena and M Sasikumar. October 07. Fusion of Geometric, Positional and Moments features for Handwritten Character Recognition using Neural Network, In National Conference on Computer Vision, AI and Robotics -- (NCCVAIR - 07) at Chennai. India. Pages 74--80.

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Ragha Leena and M Sasikumar. March 2009. Dynamic presprocessing and feature analysis for handwritten character recognition in Kannada, In IEEE International Advance Computing Conference (IACC-09) at Punjab, India. pages 3183--3188.

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Cited By

Patel MParikh SPatel A(2021)Comparative Study of Handwritten Character Recognition System for Indian LanguagesICT with Intelligent Applications10.1007/978-981-16-4177-0_78(797-806)Online publication date: 6-Dec-2021
https://doi.org/10.1007/978-981-16-4177-0_78
Anami BGarag D(2019)A Semi-automatic Methodology for Recognition of Printed Kannada Character Primitives Useful in Character ConstructionRecent Trends in Image Processing and Pattern Recognition10.1007/978-981-13-9187-3_22(244-260)Online publication date: 17-Jul-2019
https://doi.org/10.1007/978-981-13-9187-3_22
Kabir KShafin MAnannya TDebnath DKabir MIslam MSarwar H(2015)Projection-based features: A superior domain for handwritten Bangla basic characters recognition2015 IEEE 9th International Conference on Intelligent Systems and Control (ISCO)10.1109/ISCO.2015.7282258(1-7)Online publication date: Jan-2015
https://doi.org/10.1109/ISCO.2015.7282258

Index Terms

Using moments features from Gabor directional images for Kannada handwriting character recognition
1. Computer systems organization
  1. Architectures
    1. Other architectures
      1. Neural networks
2. Computing methodologies

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cover image ACM Other conferences

ICWET '10: Proceedings of the International Conference and Workshop on Emerging Trends in Technology

February 2010

1070 pages

ISBN:9781605588124

DOI:10.1145/1741906

Program Chair:
B. K. Mishra

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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UNITECH: Unitech Engineers, India
AICTE: All India Council for Technical Education

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Association for Computing Machinery

New York, NY, United States

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Published: 26 February 2010

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ICWET '10: International Conference and Workshop on Emerging Trends in Technology

February 26 - 27, 2010

Maharashtra, Mumbai, India

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Cited By

Patel MParikh SPatel A(2021)Comparative Study of Handwritten Character Recognition System for Indian LanguagesICT with Intelligent Applications10.1007/978-981-16-4177-0_78(797-806)Online publication date: 6-Dec-2021
https://doi.org/10.1007/978-981-16-4177-0_78
Anami BGarag D(2019)A Semi-automatic Methodology for Recognition of Printed Kannada Character Primitives Useful in Character ConstructionRecent Trends in Image Processing and Pattern Recognition10.1007/978-981-13-9187-3_22(244-260)Online publication date: 17-Jul-2019
https://doi.org/10.1007/978-981-13-9187-3_22
Kabir KShafin MAnannya TDebnath DKabir MIslam MSarwar H(2015)Projection-based features: A superior domain for handwritten Bangla basic characters recognition2015 IEEE 9th International Conference on Intelligent Systems and Control (ISCO)10.1109/ISCO.2015.7282258(1-7)Online publication date: Jan-2015
https://doi.org/10.1109/ISCO.2015.7282258

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