Abstract
Personal authentication through fingerprint matching merely depends on the proper identification of the minutia points of a fingerprint. In this paper, a minutia detection scheme is presented by employing gray scale hit-or-miss transformation. The work focuses exclusively on two widely used minutia points namely ridge bifurcations and ridge endings. To detect all the minutia points, a set of bifurcation shaped templates, oriented along various directions, are constructed. Ridge bifurcations are identified directly from original fingerprint through hit-or-miss transformation using the predefined templates. The ridge endings, on the other hand, are detected from the inverted image by using the same set of templates. The proposed method is implemented and tested on real fingerprint images. The experimental results show the efficiency and accuracy of the method. A comparative study is also provided between the proposed method and other relevant techniques which proves the efficacy of the method.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Arpit, D., Namboodiri, A.: Fingerprint feature extraction from gray scale images by ridge tracing. In: 2011 International Joint Conference on Biometrics (IJCB), pp. 1–8. IEEE (2011)
Bansal, R., Sehgal, P., Bedi, P.: Effective morphological extraction of true fingerprint minutiae based on the hit or miss transform. Int. J. Biom. Bioinform. (IJBB) 4(2), 71–85 (2010)
Bansal, R., Sehgal, P., Bedi, P.: Effective morphological extraction of true fingerprint minutiae based on the hit or miss transform. Int. J. Biom. Bioinform. (IJBB) 4(2), 71–85 (2010)
Barat, C., Ducottet, C., Jourlin, M.: Pattern matching using morphological probing. In: Proceedings 2003 International Conference on Image Processing, ICIP 2003, vol. 1, pp. 369–372. IEEE (2003)
Bhanu, B., Boshra, M., Tan, X.: Logical templates for feature extraction in fingerprint images. In: Proceedings of 15th International Conference on Pattern Recognition, vol. 2, pp. 846–850. IEEE (2000)
Bhanu, B., Tan, X.: Learned templates for feature extraction in fingerprint images. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol. 2, pp. 591–596 (2001)
Bresenham, J.E.: Algorithm for computer control of a digital plotter. IBM Syst. J. 4(1), 25–30. IBM Corporation (1965)
Chikkerur, S., Wu, C., Govindaraju, V.: A systematic approach for feature extraction in fingerprint images. In: Biometric Authentication, pp. 344–350. Springer (2004)
Farina, A., Kovacs-Vajna, Z.M., Leone, A.: Fingerprint minutiae extraction from skeletonized binary images, Pattern Recogn. 32(5), 877–889. Elsevier (1999)
Feng, J.: Combining minutiae descriptors for fingerprint matching. Pattern Recogn. 41(1), 342–352. Elsevier (2008)
Fronthaler, H., Kollreider, K., Bigun, J.: Local feature extraction in fingerprints by complex filtering. In: Advances in Biometric Person Authentication, pp. 77–84. Springer (2005)
Fronthaler, H., Kollreider, K., Bigun, J.: Local features for enhancement and minutiae extraction in fingerprints. IEEE Trans. Image Process. 17(3), 354–363 (2008)
Fronthaler, H., Kollreider, K., Bigun, J.: Local features for enhancement and minutiae extraction in fingerprints. IEEE Trans. Image Process. 17(3), 354–363 (2008)
Gao, X., Chen, X., Cao, J., Deng, Z., Liu, C., Feng, J.: A novel method of fingerprint minutiae extraction based on Gabor phase. In: 2010 17th IEEE International Conference on Image Processing (ICIP), pp. 3077–3080 (2010)
Gao, Q., Moschytz, G.S.: Fingerprint feature extraction using CNNs. Eur. Conf. Circuit Theory Des. 1, 97–100 (2001)
Hong, L., Wan, Y., Jain, A.K.: Fingerprint image enhancement: algorithm and performance evaluation. IEEE Trans. Pattern Anal. Mach. Intell. 20(8), 777–789 (1998)
Hong, L., Wan, Y., Jain, A.K.: Fingerprint image enhancement: algorithm and performance evaluation. IEEE Trans. Pattern Anal. Mach. Intell. 20(8), 777–789 (1998)
Jiang, X., Yau, W. Y., Ser, W.: Detecting the fingerprint minutiae by adaptive tracing the gray-level ridge. Pattern Recogn. 34(5), 999–1013. Elsevier (2001)
Khosravi, M., Schafer, R.W.: Template matching based on a grayscale hit-or-miss transform. IEEE Trans. Image Process. 5(6), 1060–1066 (1996)
Khosravi, M., Schafer, R.W.: Template matching based on a grayscale hit-or-miss transform. IEEE Trans. Image Process. 5(6), 1060–1066 (1996)
Maio, D., Maltoni, D., Cappelli, R., Wayman, J.L., Jain, A.K.: FVC2004: Third Fingerprint Verification Competition. Biometric Authentication, pp. 1–7. Springer (2004)
Miao, D., Tang, Q., Fu, W.: Fingerprint minutiae extraction based on principal curves. Pattern Recogn. Lett. 28(16), 2184–2189. Elsevier (2007)
Nallaperumal, K., Padmapriya, S.: A novel technique for fingerprint feature extraction using fixed size templates. In: 2005 Annual IEEE INDICON, pp. 371–374 (2005)
Nguyen, T.H., Wang, Y., Li, R.: An improved ridge features extraction algorithm for distorted fingerprints matching. J. Inf. Secur. Appl. 18(4), 206–214. Elsevier (2013)
Ratha, N.K., Chen, S., Jain, A.K.: Adaptive flow orientation-based feature extraction in fingerprint images. Pattern Recogn. 28(11), 1657–1672. Elsevier (1995)
Schaefer, R., Casasent, D.: Nonlinear optical hit—miss transform for detection. Appl. Opt. 34(20), 3869–3882. Optical Society of America (1995)
Serra, J.: Image Analysis and Mathematical Morphology. Academic Press, Inc. (1983)
Shi, Z., Govindaraju, V.: A chaincode based scheme for fingerprint feature extraction. Pattern Recogn. Lett. 27(5), 462–468. Elsevier (2006)
Shin, J.H., Hwang, H.Y., Chien, S.: Detecting fingerprint minutiae by run length encoding scheme. Pattern Recogn. 39(6), 1140–1154. Elsevier (2006)
Short, N. J., Hsiao, M. S., Fox, E.: Robust feature extraction in fingerprint images using ridge model tracking. In: 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS), pp. 259–264. IEEE (2012)
Simon-Zorita, D., Ortega-Garcia, J., Cruz-Llanas, S., Gonzalez-Rodriguez, J.: Minutiae extraction scheme for fingerprint recognition systems. In: Proceedings 2001 International Conference on Image Processing, vol. 3, pp. 254–257. IEEE (2001)
Tiwari, S., Sharma, N.: Q-Learning approach for minutiae extraction from fingerprint image. Procedia Technol. (6), 82–89. Elsevier (2012)
Yang, J., Liu, L., Jiang, T.: Improved Method for Extraction of Fingerprint Features 552–558, (2002)
Zhao, F., Tang, X.: Preprocessing and postprocessing for skeleton-based fingerprint minutiae extraction. Pattern Recogn. 40(4), 1270–1281. Elsevier (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Das, D. (2020). A Minutia Detection Approach from Direct Gray-Scale Fingerprint Image Using Hit-or-Miss Transformation. In: Das, A., Nayak, J., Naik, B., Pati, S., Pelusi, D. (eds) Computational Intelligence in Pattern Recognition. Advances in Intelligent Systems and Computing, vol 999. Springer, Singapore. https://doi.org/10.1007/978-981-13-9042-5_17
Download citation
DOI: https://doi.org/10.1007/978-981-13-9042-5_17
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-9041-8
Online ISBN: 978-981-13-9042-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)