Fingerprint classification using singular points and Fourier image

Mohammad Rahmati; Ali Jannatpour

doi:10.1117/12.365867

18 October 1999 Fingerprint classification using singular points and Fourier image

Mohammad Rahmati, Ali Jannatpour

Proceedings Volume 3808, Applications of Digital Image Processing XXII; (1999) https://doi.org/10.1117/12.365867
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

Singular points are one of the characteristic features of fingerprint images. In this paper, a new way of finding these singular points from the directional image is proposed. The image used in this system is a 256 X 256 rectangular image from which the hexagonal image will be extracted. After producing the directional image, two other images will be constructed for the core & delta candidate points. These pair of points will be selected using a method based on Hough transform and local maximum algorithm. Based on the position and number of these points a one-byte code will be assigned to that class. By performing the Fourier image of the original picture, an eight-byte code will be assigned to the image using a 4 X 4 wedge-ring detector applied to the transformed image. These codes will be used to show the dissimilarity among similar images.

Citation Download Citation

Mohammad Rahmati and Ali Jannatpour "Fingerprint classification using singular points and Fourier image", Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); https://doi.org/10.1117/12.365867

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