Description

In this method, the finger print matching is the process of recognizing the finger print from one person to another person. In general, the finger print is the finger biometric feature, which is widely used for the identification purpose. Hence to identify the differentiation of the each person, finger print recognition technique is widely used. In this finger print matching process, the minutiae detection plays a major role to identify the maximum matching point of the finger print of the input image to the train dataset. In this finger print matching method, the segmentation is based on the thresholding algorithm. By using the thresholding algorithm, the region of interest ROI area is segmented and then the minutiae of the maximum matching point is detected on that region. Then the features are extracted from the ridged surface of the image. The centroid value of each ride is calculated from the input image and the minutia of each ridge is detected. At finally, the distance between the each ridge is calculated from the image. When the region of interest is segmented from the input image, then the orientation of the rigid surface is calculated for the each surface. These orientations are detected based on the centroid value of the rigid surface as well as the minutia detection of the each rigid surface. This orientation is classified into two major types, they are termination orientation and the bifurcation orientation. These are the steps which undertaken by this process. These are mainly focus to eliminate the false matching point of the finger print. On the other hand also to reduce the time consumption of the finger print matching system.