This paper presents a prototype automatic identity-authentication system using fingerprints. The system includes an improved minutiae-extraction algorithm and an alignment-based minutiae-matching algorithm. The system is tested on the Michigan State University and NIST 9 fingerprint databases, achieving good performance. The authentication process takes about 1.4 seconds on a Sun Ultra 1 workstation. The system is designed for verification, where a person's identity is confirmed by comparing their fingerprint with a stored template. The system uses minutiae, which are unique ridge patterns in fingerprints, for identification. The system's performance is evaluated using metrics such as false acceptance rate (FAR) and false rejection rate (FRR). The system is robust to variations in fingerprint images and can handle nonlinear deformations. The system is based on the concept of minutiae, which are extracted from fingerprint images and used for matching. The system's design includes acquisition, representation, feature extraction, and matching components. The minutiae-extraction algorithm is improved to be faster and more accurate. The minutiae-matching algorithm aligns the input and template minutiae to find correspondences without exhaustive search. The system is capable of handling variations in fingerprint images and provides a reliable method for identity verification. The system is tested on two fingerprint databases and shows good performance. The system is designed for use in various applications such as banking, access control, and government benefits distribution. The system is based on the principles of biometrics, which use physiological or behavioral characteristics for identification. The system is compared with other biometric technologies and is considered one of the most reliable and widely used biometric techniques. The system is designed to be efficient and accurate, with a focus on minimizing errors and ensuring reliable identification. The system is tested on real-world data and shows promising results in terms of performance and accuracy. The system is designed to be adaptable to different environments and is capable of handling variations in fingerprint images. The system is based on the principles of fingerprint identification, which has been used in forensics for decades. The system is designed to be a reliable and efficient method for identity verification using fingerprints.This paper presents a prototype automatic identity-authentication system using fingerprints. The system includes an improved minutiae-extraction algorithm and an alignment-based minutiae-matching algorithm. The system is tested on the Michigan State University and NIST 9 fingerprint databases, achieving good performance. The authentication process takes about 1.4 seconds on a Sun Ultra 1 workstation. The system is designed for verification, where a person's identity is confirmed by comparing their fingerprint with a stored template. The system uses minutiae, which are unique ridge patterns in fingerprints, for identification. The system's performance is evaluated using metrics such as false acceptance rate (FAR) and false rejection rate (FRR). The system is robust to variations in fingerprint images and can handle nonlinear deformations. The system is based on the concept of minutiae, which are extracted from fingerprint images and used for matching. The system's design includes acquisition, representation, feature extraction, and matching components. The minutiae-extraction algorithm is improved to be faster and more accurate. The minutiae-matching algorithm aligns the input and template minutiae to find correspondences without exhaustive search. The system is capable of handling variations in fingerprint images and provides a reliable method for identity verification. The system is tested on two fingerprint databases and shows good performance. The system is designed for use in various applications such as banking, access control, and government benefits distribution. The system is based on the principles of biometrics, which use physiological or behavioral characteristics for identification. The system is compared with other biometric technologies and is considered one of the most reliable and widely used biometric techniques. The system is designed to be efficient and accurate, with a focus on minimizing errors and ensuring reliable identification. The system is tested on real-world data and shows promising results in terms of performance and accuracy. The system is designed to be adaptable to different environments and is capable of handling variations in fingerprint images. The system is based on the principles of fingerprint identification, which has been used in forensics for decades. The system is designed to be a reliable and efficient method for identity verification using fingerprints.