Palm Vein Verification Using Multiple Features and Locality Preserving Projections
Biometrics is defined as identifying people by their physiological characteristic, such as iris pattern, fingerprint, and face, or by some aspects of their behavior, such as voice, signature, and gesture. Considerable attention has been drawn on these issues during the last several decades. And many...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/246083 |
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| author | Ali Mohsin Al-juboori Wei Bu Xiangqian Wu Qiushi Zhao |
| author_facet | Ali Mohsin Al-juboori Wei Bu Xiangqian Wu Qiushi Zhao |
| author_sort | Ali Mohsin Al-juboori |
| collection | DOAJ |
| description | Biometrics is defined as identifying people by their physiological characteristic, such as iris pattern, fingerprint, and face, or by some aspects of their behavior, such as voice, signature, and gesture. Considerable attention has been drawn on these issues during the last several decades. And many biometric systems for commercial applications have been successfully developed. Recently, the vein pattern biometric becomes increasingly attractive for its uniqueness, stability, and noninvasiveness. A vein pattern is the physical distribution structure of the blood vessels underneath a person’s skin. The palm vein pattern is very ganglion and it shows a huge number of vessels. The attitude of the palm vein vessels stays in the same location for the whole life and its pattern is definitely unique. In our work, the matching filter method is proposed for the palm vein image enhancement. New palm vein features extraction methods, global feature extracted based on wavelet coefficients and locality preserving projections (WLPP), and local feature based on local binary pattern variance and locality preserving projections (LBPV_LPP) have been proposed. Finally, the nearest neighbour matching method has been proposed that verified the test palm vein images. The experimental result shows that the EER to the proposed method is 0.1378%. |
| format | Article |
| id | doaj-art-19f434c4b6ca4b3e8e2af470b3389ec3 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-19f434c4b6ca4b3e8e2af470b3389ec32025-08-20T03:54:21ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/246083246083Palm Vein Verification Using Multiple Features and Locality Preserving ProjectionsAli Mohsin Al-juboori0Wei Bu1Xiangqian Wu2Qiushi Zhao3School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, ChinaDepartment of New Media Technology and Arts, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, ChinaBiometrics is defined as identifying people by their physiological characteristic, such as iris pattern, fingerprint, and face, or by some aspects of their behavior, such as voice, signature, and gesture. Considerable attention has been drawn on these issues during the last several decades. And many biometric systems for commercial applications have been successfully developed. Recently, the vein pattern biometric becomes increasingly attractive for its uniqueness, stability, and noninvasiveness. A vein pattern is the physical distribution structure of the blood vessels underneath a person’s skin. The palm vein pattern is very ganglion and it shows a huge number of vessels. The attitude of the palm vein vessels stays in the same location for the whole life and its pattern is definitely unique. In our work, the matching filter method is proposed for the palm vein image enhancement. New palm vein features extraction methods, global feature extracted based on wavelet coefficients and locality preserving projections (WLPP), and local feature based on local binary pattern variance and locality preserving projections (LBPV_LPP) have been proposed. Finally, the nearest neighbour matching method has been proposed that verified the test palm vein images. The experimental result shows that the EER to the proposed method is 0.1378%.http://dx.doi.org/10.1155/2014/246083 |
| spellingShingle | Ali Mohsin Al-juboori Wei Bu Xiangqian Wu Qiushi Zhao Palm Vein Verification Using Multiple Features and Locality Preserving Projections The Scientific World Journal |
| title | Palm Vein Verification Using Multiple Features and Locality Preserving Projections |
| title_full | Palm Vein Verification Using Multiple Features and Locality Preserving Projections |
| title_fullStr | Palm Vein Verification Using Multiple Features and Locality Preserving Projections |
| title_full_unstemmed | Palm Vein Verification Using Multiple Features and Locality Preserving Projections |
| title_short | Palm Vein Verification Using Multiple Features and Locality Preserving Projections |
| title_sort | palm vein verification using multiple features and locality preserving projections |
| url | http://dx.doi.org/10.1155/2014/246083 |
| work_keys_str_mv | AT alimohsinaljuboori palmveinverificationusingmultiplefeaturesandlocalitypreservingprojections AT weibu palmveinverificationusingmultiplefeaturesandlocalitypreservingprojections AT xiangqianwu palmveinverificationusingmultiplefeaturesandlocalitypreservingprojections AT qiushizhao palmveinverificationusingmultiplefeaturesandlocalitypreservingprojections |