Bimodal biometric verification using the fusion of palmprint and infrared palm-dorsum vein images

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Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106402

Title:	Bimodal biometric verification using the fusion of palmprint and infrared palm-dorsum vein images
Authors:	范國清;Lin, Chih-Lung;Wang, Shih-Hung;Cheng, Hsu-Yung;Fan, Kuo-Chin;Hsu, Wei-Lieh;Lai, Chin-Rong
Contributors:	資訊電機學院資訊工程學系
Keywords:	Algorithms;Biometric Identification - methods;biometric verification;Dermatoglyphics;discrete wavelet transform;Hand - anatomy & histology;Hand - blood supply;Humans;image fusion;Image Processing, Computer-Assisted - methods;palmprint;Support Vector Machine;vein pattern;Wavelet Analysis
Date:	2015-12-12
Issue Date:	2026-04-23 13:20:22 (UTC+8)
Publisher:	MDPI Multidisciplinary Digital Publishing Institute;Switzerland: MDPI
Abstract:	摘要： In this paper, we present a reliable and robust biometric verification method based on bimodal physiological characteristics of palms, including the palmprint and palm-dorsum vein patterns. The proposed method consists of five steps: (1) automatically aligning and cropping the same region of interest from different palm or palm-dorsum images; (2) applying the digital wavelet transform and inverse wavelet transform to fuse palmprint and vein pattern images; (3) extracting the line-like features (LLFs) from the fused image; (4) obtaining multiresolution representations of the LLFs by using a multiresolution filter; and (5) using a support vector machine to verify the multiresolution representations of the LLFs. The proposed method possesses four advantages: first, both modal images are captured in peg-free scenarios to improve the user-friendliness of the verification device. Second, palmprint and vein pattern images are captured using a low-resolution digital scanner and infrared (IR) camera. The use of low-resolution images results in a smaller database. In addition, the vein pattern images are captured through the invisible IR spectrum, which improves antispoofing. Third, since the physiological characteristics of palmprint and vein pattern images are different, a hybrid fusing rule can be introduced to fuse the decomposition coefficients of different bands. The proposed method fuses decomposition coefficients at different decomposed levels, with different image sizes, captured from different sensor devices. Finally, the proposed method operates automatically and hence no parameters need to be set manually. Three thousand palmprint images and 3000 vein pattern images were collected from 100 volunteers to verify the validity of the proposed method. The results show a false rejection rate of 1.20% and a false acceptance rate of 1.56%. It demonstrates the validity and excellent performance of our proposed method comparing to other methods. 其他題名： Sensors (Basel) 出版者： Switzerland: MDPI 出版日期： 2015-12-12 出處： Sensors (Basel, Switzerland), 2015-12, Vol.15 (12), p.31339-31361 資源來源： ProQuest Open Access Content Collection 版權： 2015 by the authors; licensee MDPI, Basel, Switzerland. 2015 識別號： ISSN: 1424-8220 識別號： EISSN: 1424-8220 識別號： DOI: 10.3390/s151229856 識別號： PMID: 26703596
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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