Handwritten signature verification based on neural 'Gas' based vector quantization

被引：0

作者：

Zhang, BL ^{[1
]}

Fu, MY ^{[1
]}

Yan, H ^{[1
]}

机构：

[1] Univ Newcastle, Dept Elect & Comp Engn, Callaghan, NSW 2308, Australia

来源：

FOURTEENTH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1 AND 2 | 1998年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper propose a vector quantization (VQ) technique to solve the problem of handwritten signature verification. A neural 'gas' model is trained to establish a reference set Sor each registered person with handwritten signature samples. Then a test sample is compared with all the prototypes in the reference set and the system outputs the label of the writer of the word. Several different feature extraction methods are compared and goad results have been obtained by the VQ technique.

引用

页码：1862 / 1864

页数：3

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