Article

Gabor Feature Extraction for Character Recognition: Comparison with Gradient Feature

Authors:

Cheng-Lin Liu,

Masashi Koga,

Hiromichi FujisawaAuthors Info & Claims

ICDAR '05: Proceedings of the Eighth International Conference on Document Analysis and Recognition

Pages 121 - 125

https://doi.org/10.1109/ICDAR.2005.119

Published: 31 August 2005 Publication History

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Abstract

Gabor filter feature has been applied to character recognition but was not compared with the best direction feature: gradient feature. In this paper, we propose a principled method for implementing Gabor filters for character feature extraction and compare the recognition performances of Gabor feature and gradient feature on three databases. The results show that Gabor filters with low orientation sensitivity and broad frequency band favor recognition accuracy. The Gabor feature performs comparably or better than the gradient feature on two of the three databases, but is inferior on the rest one.

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Gabor Feature Extraction for Character Recognition: Comparison with Gradient Feature

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ICDAR '05: Proceedings of the Eighth International Conference on Document Analysis and Recognition

August 2005

1264 pages

ISBN:0769524206

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IEEE Computer Society

United States

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Published: 31 August 2005

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Chen JCao HNatarajan P(2015)Integrating natural language processing with image document analysisInternational Journal on Document Analysis and Recognition10.1007/s10032-015-0247-x18:3(235-247)Online publication date: 1-Sep-2015
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Su TZhang TGuan DHuang H(2007)Gabor-based recognizer for Chinese handwriting from segmentation-free strategyProceedings of the 12th international conference on Computer analysis of images and patterns10.5555/1770904.1770978(539-546)Online publication date: 27-Aug-2007
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Liu C(2007)Normalization-Cooperated Gradient Feature Extraction for Handwritten Character RecognitionIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2007.109029:8(1465-1469)Online publication date: 1-Aug-2007
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