Year 2023,
, 29 - 39, 21.06.2023
Mustafa Kocakulak
,
Nurettin Acır
References
- [1] Zhang, L., Li, L., Yang, A., Shen, Y., Yang, M. (2017). Towards contactless palmprint recognition: A novel device, a new benchmark, and a collaborative representation based identification approach.
Pattern Recognition, 69, 199–212.
- [2] Ong Michael, G. K., Connie, T., Jin Teoh, A. B. (2008). Touch-less palm print biometrics: Novel design and implementation. Image and Vision Computing, 26(12), 1551–1560.
- [3] Zhang, D., Kong, W. K., You, J., Wong, M. (2003). Online palmprint identification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(9), 1041–1050.
- [4] Kekre, H. B., Sarode, T., Vig, R. (2012). An effectual method for extraction of ROI of palmprints. Proceedings - 2012 International Conference on Communication, Information and Computing
Technology, ICCICT 2012, 12–16.
- [5] Damak, W., Trabelsi, R. B., Damak, M. A., Sellami, D. (2018). Dynamic ROI extraction method for hand vein images. IET Computer Vision, 12(5), 586–595.
- [6] Lu, H., Wang, Y., Gao, R., Zhao, C., Li, Y. (2021). A novel roi extraction method based on the characteristics of the original finger vein image. Sensors, 21(13).
- [7] Yang, L., Yang, G., Zhou, L., Yin, Y. (2015). Superpixel based finger vein ROI extraction with sensor interoperability. Proceedings of 2015 International Conference on Biometrics, ICB 2015, 444–451.
- [8] Li, W. X., Xia, S. X., Zhang, D. P., & Zhuo-Qun, X. U. (2004). A new palmprint identification method using bi-directional matching based on major line features. Journal of computer research and
development, 41(6), 996-1002.
- [9] Poon, C., Wong, D. C. M., Shen, H. C. (2004). A new method in locating and segmenting palmprint into region-of-interest. Proceedings - International Conference on Pattern Recognition, 4, 533–
536.
- [10] Wang, L., Leedham, G., Siu-Yeung Cho, D. (2008). Minutiae feature analysis for infrared hand vein pattern biometrics. Pattern Recognition, 41(3), 920–929.
- [11] Lin, S., Xu, T., Yin, X. (2017). Region of interest extraction for palmprint and palm vein recognition. Proceedings - 2016 9th International Congress on Image and Signal Processing, BioMedical
Engineering and Informatics, CISP-BMEI 2016, (4), 538–542.
- [12] Jaswal, G., Kaul, A., Nath, R. (2017). Palm print ROI extraction using Bresenham line algorithm. 4th IEEE International Conference on Signal Processing, Computing and Control, ISPCC 2017, 2017-Janua, 547–552.
- [13] Yan, M., Sun, D., Zhao, S., & Zhou, J. (2013, November). A robust approach for palm ROI extraction based on real-time region learning. In Chinese Conference on Biometric Recognition (pp. 241-
248). Springer, Cham.
- [14] Kocakulak, M., & Acir, N. (2022, May). Dynamic ROI Extraction for Palmprints using MediaPipe Hands. In 2022 30th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4).
IEEE.
- [15] Zhang, F., Bazarevsky, V., Vakunov, A., Tkachenka, A., Sung, G., Chang, C.-L., & Grundmann, M. (2020). MediaPipe Hands: On-device Real-time Hand Tracking. http://arxiv.org/abs/2006.10214
- [16] Sun, Z., Tan, T., Wang, Y., Li, S. Z. (2005). Ordinal palmprint represention for personal identification. Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern
Recognition, CVPR 2005, I, 279–284.
- [17] Hao, Y., Sun, Z., Tan, T., & Ren, C. (2008, October). Multispectral palm image fusion for accurate contact-free palmprint recognition. In 2008 15th IEEE International Conference on Image
Processing (pp. 281-284). IEEE.
- [18] Kumar, A. (2019). Toward More Accurate Matching of Contactless Palmprint Images under Less Constrained Environments. IEEE Transactions on Information Forensics and Security, 14(1), 34–47.
- [19] Kumar, A. (2008). Incorporating cohort information for reliable palmprint authentication. Proceedings - 6th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2008,
583–590.
- [20] Dai, J., Feng, J., Zhou, J. (2012). Robust and efficient ridge-based palmprint matching. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(8), 1618–1632.
- [21] Chen, W. S., Chiang, Y. S., Chiu, Y. H. (2007). Biometric verification by fusing hand geometry and palmprint. Proceedings - 3rd International Conference on Intelligent Information Hiding and
Multimedia Signal Processing, IIHMSP 2007., 2, 403–406.
- [22] Poinsot, A., Yang, F., Paindavoine, M. (2009). Small sample biometric recognition based on palmprint and face fusion. 4th International Multi-Conference on Computing in the Global Information
Technology, ICCGI 2009, 118–122.
- [23] Michael, G. K. O., Connie, T., Teoh Beng Jin, A. (2010). An innovative contactless palm print and knuckle print recognition system. Pattern Recognition Letters, 31(12), 1708–1719.
- [24] Ferrer, M. A., Vargas, F., Morales, A. (2011). BiSpectral contactless hand based biometric system. 2011 2nd National Conference on Telecommunications, CONATEL 2011 - Proceedings.
- [25] Morales, A., Ferrer, M. A., Travieso, C. M., Alonso, J. B. (2012). Multisampling approach applied to contactless hand biometrics. Proceedings - International Carnahan Conference on Security
Technology, 224–229.
- [26] Aykut, M., Ekinci, M. 2015. Developing a contactless palmprint authentication system by introducing a novel ROI extraction method. Image and Vision Computing, 40, 65–74.
- [27] Xiao, Q., Lu, J., Jia, W., & Liu, X. (2019). Extracting palmprint ROI from whole hand image using straight line clusters. IEEE Access, 7, 74327-74339.
- [28] Liang, X., Li, Z., Fan, D., Li, J., Jia, W., & Zhang, D. (2022). Touchless palmprint recognition based on 3D Gabor template and block feature refinement. Knowledge-Based Systems, 249, 108855.
- [29] Lugaresi, C., Tang, J., Nash, H., McClanahan, C., Uboweja, E., Hays, M., Zhang, F., Chang, C.-L., Yong, M. G., Lee, J., Chang, W.-T., Hua, W., Georg, M., & Grundmann, M. (2019). MediaPipe: A Framework
for Building Perception Pipelines. http://arxiv.org/abs/1906.08172
- [30] Yakno, M., Mohamad-Saleh, J., and Rosdi, B. A. (2015, May). New technique for larger ROI extraction of hand vein images. In 2015 International Conference on BioSignal Analysis, Processing and
Systems (ICBAPS) (pp. 82-87). IEEE.
A Contactless Palmprint Imaging System Design Using Mediapipe Hands
Year 2023,
, 29 - 39, 21.06.2023
Mustafa Kocakulak
,
Nurettin Acır
Abstract
Palmprint has been widely used in biometric systems because of its durability and reliability. To avoid recognition performance degradation, dynamic region of interest extraction is a critical step for these systems. In this study, a low-cost contactless palmprint imaging system has been designed and a dynamic region of interest extraction method has been applied to palmprints using the MediaPipe Hands framework. Since the need for hygienic touchless systems has been realized in the post-COVID-19 pandemic world, a low-cost imaging system has been proposed to capture the user’s hand at a distance without touching any platform. The region of interest of the user's palmprints in a real-time video stream has been extracted dynamically. This study creates a paradigm for future studies on palmprint imaging. With conducted experiments, the potential of MediaPipe Hands in terms of speed and accuracy on mobile palmprint imaging applications has been realized on Raspberry Pi 4. This work demonstrates that the employed hardware and proposed hand-tracking algorithm are suitable for designing low-cost contactless palmprint imaging systems in non-controlled ambient light conditions. For recognition purposes, a database will be released soon.
References
- [1] Zhang, L., Li, L., Yang, A., Shen, Y., Yang, M. (2017). Towards contactless palmprint recognition: A novel device, a new benchmark, and a collaborative representation based identification approach.
Pattern Recognition, 69, 199–212.
- [2] Ong Michael, G. K., Connie, T., Jin Teoh, A. B. (2008). Touch-less palm print biometrics: Novel design and implementation. Image and Vision Computing, 26(12), 1551–1560.
- [3] Zhang, D., Kong, W. K., You, J., Wong, M. (2003). Online palmprint identification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(9), 1041–1050.
- [4] Kekre, H. B., Sarode, T., Vig, R. (2012). An effectual method for extraction of ROI of palmprints. Proceedings - 2012 International Conference on Communication, Information and Computing
Technology, ICCICT 2012, 12–16.
- [5] Damak, W., Trabelsi, R. B., Damak, M. A., Sellami, D. (2018). Dynamic ROI extraction method for hand vein images. IET Computer Vision, 12(5), 586–595.
- [6] Lu, H., Wang, Y., Gao, R., Zhao, C., Li, Y. (2021). A novel roi extraction method based on the characteristics of the original finger vein image. Sensors, 21(13).
- [7] Yang, L., Yang, G., Zhou, L., Yin, Y. (2015). Superpixel based finger vein ROI extraction with sensor interoperability. Proceedings of 2015 International Conference on Biometrics, ICB 2015, 444–451.
- [8] Li, W. X., Xia, S. X., Zhang, D. P., & Zhuo-Qun, X. U. (2004). A new palmprint identification method using bi-directional matching based on major line features. Journal of computer research and
development, 41(6), 996-1002.
- [9] Poon, C., Wong, D. C. M., Shen, H. C. (2004). A new method in locating and segmenting palmprint into region-of-interest. Proceedings - International Conference on Pattern Recognition, 4, 533–
536.
- [10] Wang, L., Leedham, G., Siu-Yeung Cho, D. (2008). Minutiae feature analysis for infrared hand vein pattern biometrics. Pattern Recognition, 41(3), 920–929.
- [11] Lin, S., Xu, T., Yin, X. (2017). Region of interest extraction for palmprint and palm vein recognition. Proceedings - 2016 9th International Congress on Image and Signal Processing, BioMedical
Engineering and Informatics, CISP-BMEI 2016, (4), 538–542.
- [12] Jaswal, G., Kaul, A., Nath, R. (2017). Palm print ROI extraction using Bresenham line algorithm. 4th IEEE International Conference on Signal Processing, Computing and Control, ISPCC 2017, 2017-Janua, 547–552.
- [13] Yan, M., Sun, D., Zhao, S., & Zhou, J. (2013, November). A robust approach for palm ROI extraction based on real-time region learning. In Chinese Conference on Biometric Recognition (pp. 241-
248). Springer, Cham.
- [14] Kocakulak, M., & Acir, N. (2022, May). Dynamic ROI Extraction for Palmprints using MediaPipe Hands. In 2022 30th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4).
IEEE.
- [15] Zhang, F., Bazarevsky, V., Vakunov, A., Tkachenka, A., Sung, G., Chang, C.-L., & Grundmann, M. (2020). MediaPipe Hands: On-device Real-time Hand Tracking. http://arxiv.org/abs/2006.10214
- [16] Sun, Z., Tan, T., Wang, Y., Li, S. Z. (2005). Ordinal palmprint represention for personal identification. Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern
Recognition, CVPR 2005, I, 279–284.
- [17] Hao, Y., Sun, Z., Tan, T., & Ren, C. (2008, October). Multispectral palm image fusion for accurate contact-free palmprint recognition. In 2008 15th IEEE International Conference on Image
Processing (pp. 281-284). IEEE.
- [18] Kumar, A. (2019). Toward More Accurate Matching of Contactless Palmprint Images under Less Constrained Environments. IEEE Transactions on Information Forensics and Security, 14(1), 34–47.
- [19] Kumar, A. (2008). Incorporating cohort information for reliable palmprint authentication. Proceedings - 6th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2008,
583–590.
- [20] Dai, J., Feng, J., Zhou, J. (2012). Robust and efficient ridge-based palmprint matching. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(8), 1618–1632.
- [21] Chen, W. S., Chiang, Y. S., Chiu, Y. H. (2007). Biometric verification by fusing hand geometry and palmprint. Proceedings - 3rd International Conference on Intelligent Information Hiding and
Multimedia Signal Processing, IIHMSP 2007., 2, 403–406.
- [22] Poinsot, A., Yang, F., Paindavoine, M. (2009). Small sample biometric recognition based on palmprint and face fusion. 4th International Multi-Conference on Computing in the Global Information
Technology, ICCGI 2009, 118–122.
- [23] Michael, G. K. O., Connie, T., Teoh Beng Jin, A. (2010). An innovative contactless palm print and knuckle print recognition system. Pattern Recognition Letters, 31(12), 1708–1719.
- [24] Ferrer, M. A., Vargas, F., Morales, A. (2011). BiSpectral contactless hand based biometric system. 2011 2nd National Conference on Telecommunications, CONATEL 2011 - Proceedings.
- [25] Morales, A., Ferrer, M. A., Travieso, C. M., Alonso, J. B. (2012). Multisampling approach applied to contactless hand biometrics. Proceedings - International Carnahan Conference on Security
Technology, 224–229.
- [26] Aykut, M., Ekinci, M. 2015. Developing a contactless palmprint authentication system by introducing a novel ROI extraction method. Image and Vision Computing, 40, 65–74.
- [27] Xiao, Q., Lu, J., Jia, W., & Liu, X. (2019). Extracting palmprint ROI from whole hand image using straight line clusters. IEEE Access, 7, 74327-74339.
- [28] Liang, X., Li, Z., Fan, D., Li, J., Jia, W., & Zhang, D. (2022). Touchless palmprint recognition based on 3D Gabor template and block feature refinement. Knowledge-Based Systems, 249, 108855.
- [29] Lugaresi, C., Tang, J., Nash, H., McClanahan, C., Uboweja, E., Hays, M., Zhang, F., Chang, C.-L., Yong, M. G., Lee, J., Chang, W.-T., Hua, W., Georg, M., & Grundmann, M. (2019). MediaPipe: A Framework
for Building Perception Pipelines. http://arxiv.org/abs/1906.08172
- [30] Yakno, M., Mohamad-Saleh, J., and Rosdi, B. A. (2015, May). New technique for larger ROI extraction of hand vein images. In 2015 International Conference on BioSignal Analysis, Processing and
Systems (ICBAPS) (pp. 82-87). IEEE.