Abstract
The fingerprint recognition approach uses a variety of techniques, each of which is based on particular criteria. Finding an effective method for fingerprint recognition is the goal of this work. The goal of this project is to provide a straightforward, high-performance fingerprint recognition method. This strategy consists of two main phases: The first step is actually collecting data from samples of human fingerprints, and the second step focuses on designing and implementing a highperformance fingerprint recognition method. The feature extraction phase, in which numerous levels of the two-dimensional discrete cosine transform (D-DCT) are utilized to generate highperformance features, was the primary focus of the implemented strategy. By combining the functions of the right and left thumbs, this strategy is carried out. According to the findings, this method achieves a high level of recognition accuracy. Choosing the security architecture and policies for a system is a difficult task that must be guided by an understanding of user behavior in the proposed work to Improve data security against darker we. Shamir cryptography is the subject of our free fuzzy vault-based fingerprint cryptosystem that makes use of highly discriminative pairpolar (P-P) minutiae structures. Our system's use of fine quantization makes it possible to use a well-known, conventional minutiae matcher right away and retain a significant amount of information about a fingerprint template. The proposed fingerprint cryptosystem outperforms other minutiae-based fingerprint cryptosystems and is highly secure when compared to a few publicly available databases.