Slap Fingerprint Segmentation for Live-Scan Devices and Ten-Print Cards

Presented here is a highly accurate and computationally efficient algorithm suitable for slap fingerprint segmentation. The main advantages of this algorithm are as follows: 1)three-order cumulant is used to roughly segment the foreground; 2)frequency domain analysis is carried out in local areas to do binarization and fine segmentation; 3)cumulative sum analysis is applied to extract the knuckle lines; 4)two shape features of the ellipse are adapted to calculate the confidence of each fingertip candidate. Experimental results show that the algorithm has the characteristic of more robustness against noise and superior precision, not only for live-scan four finger slaps but also for ten-print-card five finger slaps.