AUTOMATIC CLASSIFICATION OF FORM FEATURES BASED ON NEURAL NETWORKS AND FOURIER TRANSFORM

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.

关键词： Form identification Feature eztraction Classification Fourier Transform Neural Networks

作者: GUO-HUI HE ZHENG-MEI XIE RONG CHEN

作者单位: School of information, Wuyi University, Jiangmen, Guangdong 529020, P.R.C, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 1162-1166

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）