In this paper we have used all existing algorithms. When a fingerprint image is captured it is made pass through all the algorithms arranged in a particular order. We found that if we process a fingerprint in this particular order, the final output is good enough for minutiae detection and feature extraction. We have done many experiments on fingerprint images and found that this particular order of processing is producing better result. But for this we assume that the quality of the captured image is good enough. We have not worked on image quality enhancement. So if the input image is good our method will produce a good output. Off course this is a limitation of our proposed method, but if image is captured using a good quality device, then our method will produce an equal quality output as in other existing techniques.

This paper presents a simple and novel algorithm for minutiae matching in fingerprint images. After correct detection of all minutiae in two fingerprint images, the algorithm iteratively processes each minutiae point from two images and tries to find out the number of common points on the basis of structural similarity among them. We try to find all matching pairs of minutiae between two fingerprint images with reference to a pair of chosen reference point. Once all the common minutiae points identified, the matching score can be calculated using various existing formulas.