Abstract
Highly expensive capturing devices and barely existent high-resolution palmprint datasets have slowed the development of forensic palmprint biometric systems in comparison with civilian systems. These issues are addressed in this work. The feasibility of using document scanners as a cheaper option to acquire palmprints for minutiae-based matching systems is explored. A new high-resolution palmprint dataset was established using an industry-standard Green Bit MC517 scanner and an HP Scanjet G4010 document scanner. Furthermore, a new enhancement algorithm to attenuate the negative effect of creases in the process of minutiae extraction is proposed. Experimental results highlight the potentialities of document scanners for forensic applications. Advantages and disadvantages of both technologies are discussed in this context as well.
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Aguado-Martínez M, Hernández-Palancar J, Castillo-Rosado K, Kauba C, Kirchgasser S, Uhl A (2019) On using document scanners for minutiae-based palmprint recognition. In: Progress in pattern recognition, image analysis, computer vision, and applications: 24th Iberoamerican congress, CIARP 2019, Havana, Cuba, October 28–31, 2019, Proceedings, vol 11896, p 219. Springer Nature
Cappelli R, Ferrara M, Maio D (2012) A fast and accurate palmprint recognition system based on minutiae. IEEE Trans Syst Man Cybern B 42(3):956–962
Choraś M, Kozik R (2012) Contactless palmprint and knuckle biometrics for mobile devices. Pattern Anal Appl 15(1):73–85
Dai J, Zhou J (2011) Multifeature-based high-resolution palmprint recognition. IEEE Trans Pattern Anal Mach Intell 33(5):945–957
Derawi MO, Yang B, Busch C (2011) Fingerprint recognition with embedded cameras on mobile phones. In: International conference on security and privacy in mobile information and communication systems, pp 136–147. Springer
Ester M, Kriegel HP, Sander J, Xu X et al (1996) A density-based algorithm for discovering clusters in large spatial databases with noise. KDD 96:226–231
Fei L, Lu G, Jia W, Teng S, Zhang D (2018) Feature extraction methods for palmprint recognition: a survey and evaluation. IEEE Trans Syst Man Cybern Syst 49(2):346–363
Fei L, Xu Y, Teng S, Zhang W, Tang W, Fang X (2017) Local orientation binary pattern with use for palmprint recognition. In: Chinese conference on biometric recognition, pp 213–220. Springer
Fei L, Zhang B, Zhang W, Teng S (2019) Local apparent and latent direction extraction for palmprint recognition. Inf Sci 473:59–72
Feng J, Jain AK (2011) Fingerprint reconstruction: from minutiae to phase. IEEE Trans Pattern Anal Mach Intell 33(2):209–223
Genovese A, Piuri V, Plataniotis KN, Scotti F (2019) PalmNet: Gabor-PCA convolutional networks for touchless palmprint recognition. IEEE Trans Inf Forensic Secur 14:3160–3174
Green-Bit: Green-bit mc517 scanner, http://www.greenbit-china.cn/index.php?m=content&c=index&a=show&catid=36&id=17
Hernandez-Palancar J, Munoz-Briseno A, Gago-Alonso A (2014) Using a triangular matching approach for latent fingerprint and palmprint identification. Int J Pattern Recognit Artif Intell 28(07):1460004
Hiew B, Teoh AB, Ngo DC (2006) Preprocessing of fingerprint images captured with a digital camera. In: 2006 9th international conference on control, automation, robotics and vision, pp 1–6. IEEE
HP-Inc: Hp scanjet g4010 series scanner, https://support.hp.com/us-en/document/c00817232
Jain A, Demirkus M (2008) On latent palmprint matching. Tech. Rep. 48824, Michigan State University
Jain AK, Feng J (2009) Latent palmprint matching. IEEE Trans Pattern Anal Mach Intell 31(6):1032–1047
Khan S, Waqas A, Khan MA, Ahmad AW (2018) A camera-based fingerprint registration and verification method. Int J Comput Sci Netw Secur 18(11):26–31
Kumar A, Wong DC, Shen HC, Jain AK (2003) Personal verification using palmprint and hand geometry biometric. In: International conference on audio-and video-based biometric person authentication, pp 668–678. Springer
Lee C, Lee S, Kim J, Kim SJ (2006) Preprocessing of a fingerprint image captured with a mobile camera. In: International conference on biometrics, pp 348–355. Springer
Maio D, Maltoni D, Cappelli R, Wayman JL, Jain AK (2002) Fvc2002: second fingerprint verification competition. In: Object recognition supported by user interaction for service robots, vol 3, pp 811–814. IEEE
Maltoni D, Maio D, Jain AK, Prabhakar S (2009) Handbook of fingerprint recognition. Springer Science & Business Media
Morales A, Ferrer MA, Kumar A (2011) Towards contactless palmprint authentication. IET Comput Vis 5(6):407–416
Neurotechnology-Inc: Megamatcher (sdk), https://www.neurotechnology.com/cgi-bin/biometric-components.cgi?ref=mm&component=palm-mat
Neurotechnology-Inc (2004) Verifinger 4.2 (sdk), http://www.neurotechnologija.com/download.html
Osher S, Sethian JA (1988) Fronts propagating with curvature-dependent speed: algorithms based on hamilton-jacobi formulations. J Comput Phys 79(1):12–49
Parihar AS, Kumar A, Verma OP, Gupta A, Mukherjee P, Vatsa D (2013) Point based features for contact-less palmprint images. In: 2013 IEEE International conference on technologies for homeland security (HST), pp 165–170. IEEE
Reza AM (2004) Realization of the contrast limited adaptive histogram equalization (clahe) for real-time image enhancement. J VLSI Signal Process Syst Signal Image Video Technol 38(1):35–44
Uhl A, Wild P (2008) Personal recognition using single-sensor multimodal hand biometrics. In: International conference on image and signal processing, pp 396–404. Springer
Uhl A, Wild P (2013) Experimental evidence of ageing in hand biometrics. In: 2013 international conference of the BIOSIG Special Interest Group (BIOSIG), pp 1–6. IEEE
Wang R, Ramos D, Fierrez J (2011) Latent-to-full palmprint comparison based on radial triangulation under forensic conditions. In: 2011 International joint conference on biometrics (IJCB), pp 1–6. IEEE
Wang W, Li J, Huang F, Feng H (2008) Design and implementation of log-gabor filter in fingerprint image enhancement. Pattern Recogn Lett 29(3):301–308
Whitaker J (2005) The electronics handbook, 2nd edn. CRC Press
Wu X, Zhao Q, Bu W (2014) A sift-based contactless palmprint verification approach using iterative ransac and local palmprint descriptors. Pattern Recogn 47(10):3314–3326
Zhong D, Du X, Zhong K (2019) Decade progress of palmprint recognition: a brief survey. Neurocomputing 328:16–28
Zhou K, Zhou X, Yu L, Shen L, Yu S (2019) Double biologically inspired transform network for robust palmprint recognition. Neurocomputing 337:24–45
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This project was partially funded by the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 690907 (IDENTITY).
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Aguado-Martínez, M., Hernández-Palancar, J., Castillo-Rosado, K. et al. Document scanners for minutiae-based palmprint recognition: a feasibility study. Pattern Anal Applic 24, 459–472 (2021). https://doi.org/10.1007/s10044-020-00923-3
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DOI: https://doi.org/10.1007/s10044-020-00923-3