Rapid feature extraction for Bangla handwritten digit recognition

M. Zahid Hossain; M. Ashraful Amin; Hong Yan

doi:10.1109/ICMLC.2011.6017001

Rapid feature extraction for Bangla handwritten digit recognition

M. Zahid Hossain
, M. Ashraful Amin
, Hong Yan

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

14 Citations (Scopus)

Abstract

Feature extraction is one of the fundamental problems of character recognition. The performance of character recognition system is largely depending on proper feature extraction and correct classifier selection. In this article, a rapid feature extraction method is proposed and named as Celled Projection (CP) that compute the projection of each section formed through partitioning an image. The recognition performance of the proposed method is compared with other widely used feature extraction methods that are intensively studied for many different scripts in literature. The experiments have been conducted using Bangla handwritten numerals along with three different well known classifiers which demonstrate comparable results including 94.12% recognition accuracy using celled-projection. © 2011 IEEE.

Original language	English
Title of host publication	Proceedings - International Conference on Machine Learning and Cybernetics
Pages	1832-1837
Volume	4
DOIs	https://doi.org/10.1109/ICMLC.2011.6017001
Publication status	Published - 2011
Event	2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011 - Guilin, Guangxi, China Duration: 10 Jul 2011 → 13 Jul 2011 https://ieeexplore.ieee.org/xpl/conhome/6009138/proceeding

Publication series

Name
Volume	4
ISSN (Print)	2160-133X
ISSN (Electronic)	2160-1348

Conference

Conference	2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011
Place	China
City	Guilin, Guangxi
Period	10/07/11 → 13/07/11
Internet address	https://ieeexplore.ieee.org/xpl/conhome/6009138/proceeding

Research Keywords

Celled projection
Character recognition
Feature extraction
Neural network

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10.1109/ICMLC.2011.6017001

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@inproceedings{8f45221f86a8456cb3b6e341bb89be59,

title = "Rapid feature extraction for Bangla handwritten digit recognition",

abstract = "Feature extraction is one of the fundamental problems of character recognition. The performance of character recognition system is largely depending on proper feature extraction and correct classifier selection. In this article, a rapid feature extraction method is proposed and named as Celled Projection (CP) that compute the projection of each section formed through partitioning an image. The recognition performance of the proposed method is compared with other widely used feature extraction methods that are intensively studied for many different scripts in literature. The experiments have been conducted using Bangla handwritten numerals along with three different well known classifiers which demonstrate comparable results including 94.12\% recognition accuracy using celled-projection. {\textcopyright} 2011 IEEE.",

keywords = "Celled projection, Character recognition, Feature extraction, Neural network",

author = "Hossain, \{M. Zahid\} and Amin, \{M. Ashraful\} and Hong Yan",

year = "2011",

doi = "10.1109/ICMLC.2011.6017001",

language = "English",

isbn = "9781457703065",

volume = "4",

pages = "1832--1837",

booktitle = "Proceedings - International Conference on Machine Learning and Cybernetics",

note = "2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011 ; Conference date: 10-07-2011 Through 13-07-2011",

url = "https://ieeexplore.ieee.org/xpl/conhome/6009138/proceeding",

}

Hossain, MZ, Amin, MA & Yan, H 2011, Rapid feature extraction for Bangla handwritten digit recognition. in Proceedings - International Conference on Machine Learning and Cybernetics. vol. 4, 6017001, pp. 1832-1837, 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011, Guilin, Guangxi, China, 10/07/11. https://doi.org/10.1109/ICMLC.2011.6017001

Rapid feature extraction for Bangla handwritten digit recognition. / Hossain, M. Zahid; Amin, M. Ashraful; Yan, Hong.
Proceedings - International Conference on Machine Learning and Cybernetics. Vol. 4 2011. p. 1832-1837 6017001.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Rapid feature extraction for Bangla handwritten digit recognition

AU - Hossain, M. Zahid

AU - Amin, M. Ashraful

AU - Yan, Hong

PY - 2011

Y1 - 2011

N2 - Feature extraction is one of the fundamental problems of character recognition. The performance of character recognition system is largely depending on proper feature extraction and correct classifier selection. In this article, a rapid feature extraction method is proposed and named as Celled Projection (CP) that compute the projection of each section formed through partitioning an image. The recognition performance of the proposed method is compared with other widely used feature extraction methods that are intensively studied for many different scripts in literature. The experiments have been conducted using Bangla handwritten numerals along with three different well known classifiers which demonstrate comparable results including 94.12% recognition accuracy using celled-projection. © 2011 IEEE.

AB - Feature extraction is one of the fundamental problems of character recognition. The performance of character recognition system is largely depending on proper feature extraction and correct classifier selection. In this article, a rapid feature extraction method is proposed and named as Celled Projection (CP) that compute the projection of each section formed through partitioning an image. The recognition performance of the proposed method is compared with other widely used feature extraction methods that are intensively studied for many different scripts in literature. The experiments have been conducted using Bangla handwritten numerals along with three different well known classifiers which demonstrate comparable results including 94.12% recognition accuracy using celled-projection. © 2011 IEEE.

KW - Celled projection

KW - Character recognition

KW - Feature extraction

KW - Neural network

UR - https://www.scopus.com/pages/publications/80155186766

UR - https://www.scopus.com/pages/publications/80155186766#tab=impact

U2 - 10.1109/ICMLC.2011.6017001

DO - 10.1109/ICMLC.2011.6017001

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781457703065

VL - 4

SP - 1832

EP - 1837

BT - Proceedings - International Conference on Machine Learning and Cybernetics

T2 - 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011

Y2 - 10 July 2011 through 13 July 2011

ER -

Rapid feature extraction for Bangla handwritten digit recognition

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Research Keywords

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