ГРНТИ 50.07 Теоретические основы вычислительной техники
ББК 3297 Вычислительная техника
In this article the new algorithm for palm vein recognition using multilobe differential filters is proposed. After palm vein image preprocessing vein structure is detected based on principal curvatures. The image is considered as a surface in a three-dimensional space. Some vein points are selected using the maximum principal curvature values, and the other vein points are found from starting points by moving along the direction of minimum principal curvature. Multilobe differential filters are used to extract feature maps for vein images. These filters are flexible in terms of basic lobe choice and spatial configuration of lobes. The multilobe differential filters used in the article simulate vein branch points, and Gaussian kernel is used as the basic lobe. The normalized root-mean-square error is applied for image matching. Experimental results using CASIA multi-spectral palmprint image database demonstrate the effectiveness of the proposed method. The value of EER=0.01693 is obtained.
biometrics, palm vein recognition, principal curvatures, multilobe differential filters
1. Bhilare S., Jaswal G., Kanhangad V., Nigam A. Singlesensor hand-vein multimodal biometric recognition using multiscale deep pyramidal approach //Machine Vision and Applications. - 2018. - Vol. 29. - №. 8. - Pp. 1269-1286.
2. Buades A., Coll B., Morel J. M. A non-local algorithm for image denoising //Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on. - IEEE, 2005. - Vol. 2. - Pp. 60-65.
3. CASIA Multi-Spectral Palmprint Image Database http://biometrics.idealtest.org/
4. Chai Z., Sun Z., Mendez-Vazquez H., He R., Tan T. Gabor ordinal measures for face recognition //IEEE transactions on information forensics and security. - 2013. - Vol. 9. - №. 1. - Pp. 14-26.
5. Choi J. H., Song W., Kim T., Lee S. R., Kim H. T. Finger vein extraction using gradient normalization and principal curvature //Image Processing: Machine Vision Applications II. - International Society for Optics and Photonics, 2009. - Vol. 7251. - Pp. 725111.
6. Fienup J. R. Invariant error metrics for image reconstruction //Applied optics. - 1997. - Vol. 36. - №. 32. - Pp. 8352- 8357.
7. Han W. Y., Lee J. C. Palm vein recognition using adaptive Gabor filter //Expert Systems with Applications. - 2012. - Vol. 39. - №. 18. - Pp. 13225-13234.
8. Jain A. K., Bolle R., Pankanti S. (ed.). Biometrics: personal identification in networked society. - Springer Science & Business Media, 2006. - Vol. 479.
9. Jha R. R., Thapar D., Patil S. M., Nigam A. Ubsegnet: Unified biometric region of interest segmentation network - IEEE, 2017.
10. Kang W., Wu Q. Contactless palm vein recognition using a mutual foreground-based local binary pattern //IEEE Transactions on information forensics and security. - 2014. - Vol. 9. - №. 11. - Pp. 1974-1985.
11. Ladoux P. O., Rosenberger C., Dorizzi B. Palm vein verification system based on SIFT matching //International Conference on Biometrics. - Springer, Berlin, Heidelberg, 2009. - Pp. 1290-1298.
12. Lee E. C., Jung H., Kim D. New finger biometric method using near infrared imaging //Sensors. - 2011. - Vol. 11. - №. 3. - Pp. 2319-2333.
13. Lin C. L., Chuang T. C., Fan K. C. Palmprint verification using hierarchical decomposition //Pattern Recognition. - 2005. - Vol. 38. - №. 12. - Pp. 2639-2652.
14. Matsuda Y., Miura N., Nagasaka A., Kiyomizu H., Miyatake T. Finger-vein authentication based on deformation-tolerant feature-point matching //Machine Vision and Applications. - 2016. - Vol. 27. - №. 2. - Pp. 237-250.
15. Miura N., Nagasaka A., Miyatake T. Feature extraction of finger-vein patterns based on repeated line tracking and its application to personal identification //Machine vision and applications. - 2004. - Vol. 15. - №. 4. - Pp. 194-203.
16. Otsu N. A threshold selection method from gray-level histograms //IEEE transactions on systems, man, and cybernetics. - 1979. - Vol. 9. - №. 1. - Pp. 62-66.
17. Pavelyeva, E. A. Image processing and analysis based on the use of phase information //Computer Optics. - 2018. - Vol. 42. - № 6. - Pp. 1022-1034.
18. Protsenko M. А., Pavelyeva E. A. Iris image key points descriptors based on phase congruency //ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. - 2019. - Vol. 42. - № 2/W12. - Pp. 167-171.
19. Raghavendra R., Busch C. Novel image fusion scheme based on dependency measure for robust multispectral palmprint recognition // Pattern recognition. - 2014. - Vol. 47. - №. 6. - Pp. 2205-2221.
20. Renault C., Desvignes M., Revenu M. 3D curves tracking and its application to cortical sulci detection //Image Processing, 2000. Proceedings. 2000 International Conference on. - IEEE, 2000. - Vol. 2. - Pp. 491-494.
21. Rosdi B. A., Shing C. W., Suandi S. A. Finger vein recognition using local line binary pattern //Sensors. - 2011. - Vol. 11. - №. 12. - Pp. 11357-11371.
22. Sun Z., Tan T. Ordinal measures for iris recognition //IEEE Transactions on pattern analysis and machine intelligence. - 2008. - Vol. 31. - №. 12. - Pp. 2211-2226.
23. Sun Z., Wang L., Tan T. Ordinal feature selection for iris and palmprint recognition //IEEE Transactions on Image Processing. - 2014. - Т. 23. - №. 9. - С. 3922-3934.
24. Thapar D., Jaswal G., Nigam A., Kanhangad V. PVSNet: Palm Vein Authentication Siamese Network Trained using Triplet Loss and Adaptive Hard Mining by Learning Enforced Domain Specific Features - arXiv, 2018.
25. Wang J., Yang K., Pan Z., Wang G., Li M., Li Y. MinutiaeBased Weighting Aggregation of Deep Convolutional Features for Vein Recognition - IEEE, 2018.
26. Wang L., Leedham G., Cho D. S. Y. Minutiae feature analysis for infrared hand vein pattern biometrics //Pattern recognition. - 2008. - Vol. 41. - №. 3. - Pp. 920-929.
27. Wu J. D., Liu C. T. Finger-vein pattern identification using principal component analysis and the neural network technique //Expert Systems with Applications. - 2011. - Vol. 38. - №. 5. - Pp. 5423-5427.
28. Zhou Y., Kumar A. Human identification using palm-vein images //IEEE transactions on information forensics and security. - 2011. - Vol. 6. - №. 4. - Pp. 1259-1274.
29. Zuiderveld K. Contrast limited adaptive histogram equalization //Graphics gems. - 1994. - Pp. 474-485.
