According to the fact that the basic features of a palmprint, includingprincipal lines, wrinkles and ridges, have different resolutions, in this paper we analyzepalmprints using a multi-resolution method and define a ...According to the fact that the basic features of a palmprint, includingprincipal lines, wrinkles and ridges, have different resolutions, in this paper we analyzepalmprints using a multi-resolution method and define a novel palmprint feature, which calledwavelet energy feature (WEF), based on the wavelet transform. WEF can reflect the wavelet energydistribution of the principal lines, wrinkles and ridges in different directions at differentresolutions (scales), thus it can efficiently characterize palmprints. This paper also analyses thediscriminabilities of each level WEF and, according to these discriminabilities, chooses a suitableweight for each level to compute the weighted city block distance for recognition. The experimentalresults show that the order of the discriminabilities of each level WEF, from strong to weak, is the4th, 3rd, 5th, 2nd and 1st level. It also shows that WEF is robust to some extent in rotation andtranslation of the images. Accuracies of 99.24% and 99.45% have been obtained in palmprintverification and palmprint identification, respectively. These results demonstrate the power of theproposed approach.展开更多
In this paper, a novel biometric identification system is presented toidentify a person''s identity by his/her palmprint. In contrast to existing palmprint systems forcriminal applications, the proposed system...In this paper, a novel biometric identification system is presented toidentify a person''s identity by his/her palmprint. In contrast to existing palmprint systems forcriminal applications, the proposed system targets at the civil applications, which requireidentifying a person in a large database with high accuracy in real-time. The system is constitutedby four major components: User Interface Module, Acquisition Module, Recognition Module and ExternalModule. More than 7,000 palmprint images have been collected to test the performance of the system.The system can identify 400 palms with a low false acceptance rate, 0.02%, and a high genuineacceptance rate, 98.83%. For verification, the system can operate at a false acceptance rate, 0.017%and a false rejection rate, 0.86%. The execution time for the whole process including imagecollection, preprocessing, feature extraction and matching is less than 1 second.展开更多
Palmprint recognition is an emerging biometrics technology that has attracted increasing attention in recent years. Many palmprint recognition methods have been proposed, including traditional methods and deep learnin...Palmprint recognition is an emerging biometrics technology that has attracted increasing attention in recent years. Many palmprint recognition methods have been proposed, including traditional methods and deep learning-based methods. Among the traditional methods, the methods based on directional features are mainstream because they have high recognition rates and are robust to illumination changes and small noises. However, to date, in these methods, the stability of the palmprint directional response has not been deeply studied. In this paper, we analyse the problem of directional response instability in palmprint recognition methods based on directional feature. We then propose a novel palmprint directional response stability measurement (DRSM) to judge the stability of the directional feature of each pixel. After filtering the palmprint image with the filter bank, we design DRSM according to the relationship between the maximum response value and other response values for each pixel. Using DRSM, we can judge those pixels with unstable directional response and use a specially designed encoding mode related to a specific method. We insert the DRSM mechanism into seven classical methods based on directional feature, and conduct many experiments on six public palmprint databases. The experimental results show that the DRSM mechanism can effectively improve the performance of these methods. In the field of palmprint recognition, this work is the first in-depth study on the stability of the palmprint directional response, so this paper has strong reference value for research on palmprint recognition methods based on directional features.展开更多
文摘According to the fact that the basic features of a palmprint, includingprincipal lines, wrinkles and ridges, have different resolutions, in this paper we analyzepalmprints using a multi-resolution method and define a novel palmprint feature, which calledwavelet energy feature (WEF), based on the wavelet transform. WEF can reflect the wavelet energydistribution of the principal lines, wrinkles and ridges in different directions at differentresolutions (scales), thus it can efficiently characterize palmprints. This paper also analyses thediscriminabilities of each level WEF and, according to these discriminabilities, chooses a suitableweight for each level to compute the weighted city block distance for recognition. The experimentalresults show that the order of the discriminabilities of each level WEF, from strong to weak, is the4th, 3rd, 5th, 2nd and 1st level. It also shows that WEF is robust to some extent in rotation andtranslation of the images. Accuracies of 99.24% and 99.45% have been obtained in palmprintverification and palmprint identification, respectively. These results demonstrate the power of theproposed approach.
基金山东省自然科学基金(the Natural Science Foundation of Shandong Province of China under Grant No.G2004Z01) 教育部留学回国人员科研启动基金(The Project- sponsored by SRF for ROCS+1 种基金 SEM) 山东大学信息科学与工程学院科研启动基金。
文摘In this paper, a novel biometric identification system is presented toidentify a person''s identity by his/her palmprint. In contrast to existing palmprint systems forcriminal applications, the proposed system targets at the civil applications, which requireidentifying a person in a large database with high accuracy in real-time. The system is constitutedby four major components: User Interface Module, Acquisition Module, Recognition Module and ExternalModule. More than 7,000 palmprint images have been collected to test the performance of the system.The system can identify 400 palms with a low false acceptance rate, 0.02%, and a high genuineacceptance rate, 98.83%. For verification, the system can operate at a false acceptance rate, 0.017%and a false rejection rate, 0.86%. The execution time for the whole process including imagecollection, preprocessing, feature extraction and matching is less than 1 second.
基金supported by National Science Foundation of China(No.62076086).
文摘Palmprint recognition is an emerging biometrics technology that has attracted increasing attention in recent years. Many palmprint recognition methods have been proposed, including traditional methods and deep learning-based methods. Among the traditional methods, the methods based on directional features are mainstream because they have high recognition rates and are robust to illumination changes and small noises. However, to date, in these methods, the stability of the palmprint directional response has not been deeply studied. In this paper, we analyse the problem of directional response instability in palmprint recognition methods based on directional feature. We then propose a novel palmprint directional response stability measurement (DRSM) to judge the stability of the directional feature of each pixel. After filtering the palmprint image with the filter bank, we design DRSM according to the relationship between the maximum response value and other response values for each pixel. Using DRSM, we can judge those pixels with unstable directional response and use a specially designed encoding mode related to a specific method. We insert the DRSM mechanism into seven classical methods based on directional feature, and conduct many experiments on six public palmprint databases. The experimental results show that the DRSM mechanism can effectively improve the performance of these methods. In the field of palmprint recognition, this work is the first in-depth study on the stability of the palmprint directional response, so this paper has strong reference value for research on palmprint recognition methods based on directional features.
