A Comprehensive Analysis of Minutiae Point Extraction in Biometric FingerPrint

In general, Minutiae Point (MP) extraction in the FingerPrint (FP) is a tedious process, as it directly influences the factors such as reliability, accuracy, efficiency, etc., of FP pattern matching algorithms. In this paper, we discussed the inclusive study of MP feature extraction using image processing techniques. The performance evaluation across various dimensions including noise robustness, speed in processing, accuracy, computational complexity, etc. Various methods of MP extraction are addressed and scrutinized in a detailed way with a clear-cut of how it constructively handles the consequences in the quality of images, noise, and computational overhead. The traditional algorithms we considered are Binarization, Gradient, Wavelet, Gabor-Filter Method, and direct grayscale. Also, we considered contemporary methods such as Neural-Networks, and Hough-transform, which show high performance that are represented. Additionally, we discussed the SWOT analysis of MP extraction algorithms.