WRITER VERIFICATION BASED ON GRAPHOMETRIC FEATURES USING FEED-FORWARD NEURAL NETWORK

被引：0

作者：

Romero, Carlos F. ^{[1
]}

Travieso, Carlos M. ^{[1
]}

Alonso, Jesus B. ^{[1
]}

Ferrer, Miguel A. ^{[1
]}

机构：

[1] Univ Las Palmas Gran Canaria, Technol Ctr Innovat Commun CeTIC, Signals & Commun Dept, Campus Tafira,Ed Telecomunicac,Pabellon B, Las Palmas De Gc 35017, Spain

来源：

BIOSIGNALS 2010: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING | 2010年

关键词：

Biometric systems; Writer verification; Handwriting analysis; Neural networks; Pattern recognition;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper shows a writer verification automatic system based on a set of graphometric characteristics extracted from handwritten words. That dataset has been tested with our off-line handwritten database, which consists of 110 writers with 10 samples per writer, where a sample is a dataset of 34 words. After our experiments, we have got a verification success rate of 95.63% and Equal Error Rate (EER) of 3.90% is achieved. For previous results, we have used as classifiers a Neural Network, for each writer.

引用

页码：353 / 358

页数：6

共 14 条

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