Biometric System Laboratory

Feature Extraction

Most automatic systems for fingerprint recognition are based on minutiae matching. Minutiae are essentially terminations and bifurcations of the ridge lines that constitute a fingerprint pattern. Automatic minutiae detection is an extremely critical process, especially in low-quality fingerprints where noise and contrast deficiency can originate pixel configurations similar to minutiae or hide real minutiae.

Several approaches to automatic minutiae extraction have been proposed: although rather different from one other, most of them transform fingerprint images into binary images through an ad-hoc algorithm. The images obtained are submitted to a thinning process which allows for the ridge-line thickness to be reduced to one pixel.

In 1997, BioLab introduced the first Direct Gray-scale Minutiae Detection Approach. The new method is able to extract minutiae from fingerprint patterns without the need of binarizing and thinning the ridge lines, with the advantages of being faster, more accurate and more roboust on low-quality images.

The basic idea of the method is to follow the ridge lines on the gray-scale image, by "sailing" according to the fingerprint directional image. A set of starting points is determined by superimposing a square-meshed grid on the gray-scale image. For each starting point, the algorithm keeps following the ridge lines until they terminate or intersect other ridge lines (minutiae detection). A labelling strategy is adopted to examine each ridge-line only once and locate the intersections between ridge-lines.

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Bibliography

(Click here if you are interested in any of the publications below)

	D. Maltoni, D. Maio, A.K. Jain and J. Feng, Handbook of Fingerprint Recognition (Third Edition), Springer Nature, 2022.
	D. Maltoni, D. Maio, A.K. Jain and S. Prabhakar, Handbook of Fingerprint Recognition (Second Edition), Springer (London), 2009.
	D. Maio and D. Maltoni, "Minutiae extraction and filtering from gray-scale images", in L.C. Jain, U. Halici, I. Hayashi, S.B. Lee, Intelligent Biometric Techniques in Fingerprint & Face Recognition, CRC Press, 1999. Abstract
	R. Cappelli and D. Maltoni, "On the Spatial Distribution of Fingerprint Singularities", IEEE Transactions on Pattern Analysis Machine Intelligence, vol.31, no.4, pp.742-748, April 2009. Abstract
	D. Maio and D. Maltoni, "Direct Gray-Scale Minutiae Detection in Fingerprints", IEEE Transactions on Pattern Analysis Machine Intelligence, vol.19, no.1, pp.27-40, 1997. Abstract
	R. Cappelli, D. Maltoni and F. Turroni, "Fingerprint Enhancement using Contextual Iterative Filtering", in proceedings 5th International Conference on Biometrics (ICB2012), New Delhi, India, March 2012. Abstract
	R. Cappelli, D. Maltoni and F. Turroni, "Benchmarking Local Orientation Extraction in Fingerprint Recognition", in proceedings 20th International Conference on Pattern Recognition (ICPR2010), Istanbul, pp.1144-1147, August 2010. Abstract
	R. Cappelli, D. Maio and D. Maltoni, "Semi-automatic Enhancement of Very Low Quality Fingerprints", in proceedings 6th International Symposium on Image and Signal Processing and Analysis (ISPA09), Salzburg, pp.678-683, September 2009. Abstract
	D. Maio and D. Maltoni, "Neural Network Based Minutiae Filtering in Fingerprints", in proceedings 14th International Conference on Pattern Recognition (ICPR), Brisbane (Australia), pp.1654-1658, August 1998. Abstract
	D. Maio and D. Maltoni, "Ridge-Line Density Estimation in Digital Images", in proceedings 14th International Conference on Pattern Recognition (ICPR), Brisbane (Australia), pp.534-538, August 1998. Abstract