@inproceedings{f1eb3af88ff5485aa3def64c4505dc81,
title = "Palmprint verification for images captured in peg-less scenarios",
abstract = "This paper presents a reliable and robust palmprint verification approach using palmprint feature point number (FPN). The feature verified by support vector machine (SVM). It has the advantages of capturing palm images in peg-less scenarios and by a low cost and low-resolution (100dpi) digital scanner. The low-resolution images lead a less database size. There are 4800 palmprint images were collected from 160 persons to verify the validity of the proposed approach and the results are satisfactory with 98.30% classification correct rate (CCR). Experimental results demonstrate that the proposed approach is feasible and effective in palmprint verification. Our findings will help to extend palmprint verification technologies to security access control systems.",
keywords = "Multiresolution representation, Palmprint verification, Support vector machine",
author = "Lu, {Chun Wei} and Lin, {Chih Lung} and Fan, {Kuo Chin} and Cheng, {Hsu Yung} and Juan, {Chang Jung}",
year = "2013",
doi = "10.4028/www.scientific.net/AMM.284-287.3178",
language = "???core.languages.en_GB???",
isbn = "9783037856123",
series = "Applied Mechanics and Materials",
pages = "3178--3183",
booktitle = "Innovation for Applied Science and Technology",
note = "2nd International Conference on Engineering and Technology Innovation 2012, ICETI 2012 ; Conference date: 02-11-2012 Through 06-11-2012",
}