Extremely High Compression and Identification of Fingerprint Images Using SA4 Multiwavelet Transform

Author:

Rema N. R.1,Mythili P.1

Affiliation:

1. Division of Electronics, Cochin University of Science and Technology, Kochi, Kerala, India

Abstract

The aim of any fingerprint image compression technique is to achieve a maximum amount of compression with an adequate quality compressed image which is suitable for fingerprint recognition. Currently available techniques in the literature provide 100% recognition only up to a compression ratio of 180:1. The performance of any identification technique inherently depends on the techniques with which images are compressed. To improve the identification accuracy while the images are highly compressed, a multiwavelet-based identification approach is proposed in this paper. Both decimated and undecimated coefficients of SA4 (Symmetric Antisymmetric) multiwavelet are used as features for identification. A study is conducted on the identification performance of the multiwavelet transform with various sizes of images compressed using both wavelets and multiwavelets for fair comparison. It was noted that for images with size power of 2, the decimated multiwavelet-based compression and identification give a better performance compared to other combinations of compression/identification techniques whereas for images with size not a power of 2, the undecimated multiwavelet transform gives a better performance compared to other techniques. A 100% identification accuracy was achieved for the images from NIST-4, NITGEN, FVC2002DB3_B, FVC2004DB2_B and FVC2004DB1_B databases for compression ratios up to 520:1, 210:1, 445:1, 545:1 and 1995:1, respectively.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Rolling bearing fault diagnosis based on multiple wavelet coefficient dimensionality reduction and improved residual network;Engineering Applications of Artificial Intelligence;2024-07

2. Student Attendance Management System Based on Fingerprint Identification Technology;2023 International Conference on Integrated Intelligence and Communication Systems (ICIICS);2023-11-24

3. Research on Fingerprint Recognition Algorithm;Journal of Physics: Conference Series;2022-04-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3