Automatic classification of form features based on neural networks and Fourier transform

被引：0
|
作者：
He, Guo-Hui [1 ]
Xie, Zheng-Mei [1 ]
Chen, Rong [1 ]
机构：
[1] Wuyi Univ, Sch Informat, Jiangmen 529020, Guangdong, Peoples R China
来源：
PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2008年
关键词：
form identification; feature extraction; classification; Fourier transform; neural networks;
D O I：
10.1109/ICMLC.2008.4620579
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper focuses on the identification and classification of forms in image document management system. It introduces a methodology that uses the pretreated horizontal and vertical projection of the forms for Fourier transform and the resulted power spectrum density as the eigenvector. Then We study and practice to extract the characteristics of the forms using BP neural network. This method has overcome the deficiencies caused by poor generalization or being unable to identify symmetric form structure correctly. Experiments have proved that this method can perform classification on forms with different structures, and has excellent adaptability.
引用
收藏
页码：1162 / 1166
页数：5
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