Feature Extraction of Liquid Drop Fingerprint Based on Bezier Curve Fitting

被引：0

作者：

Song Qing ^{[1
]}

Yang Lu ^{[1
]}

Du Danqing ^{[1
]}

Meng Gaojie ^{[1
]}

Mao Xuefei ^{[1
]}

机构：

[1] BUPT, Automat Sch, Beijing, Peoples R China

来源：

PROCEEDINGS 2013 INTERNATIONAL CONFERENCE ON MECHATRONIC SCIENCES, ELECTRIC ENGINEERING AND COMPUTER (MEC) | 2013年

关键词：

Bezier curve; Liquid Drop Fingerprint; feature extraction; BP neural network;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In order to effectively characterize the Liquid Drop Fingerprint (LDF) of different liquids, a new method based on Bezier curve fitting is put forward. The fitting curve is calculated by the least square method. To decrease the fitting error and the feature dimension, the Bezier curve order should be reasonably chosen, combining the particularity of LDF. Theoretical analysis and experimental results show that the eigenvector can reflect the typical differences among different kinds of liquids, and the recognition rate within current test samples is reached up to 100%.

引用

页码：1363 / 1366

页数：4