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In this study, we propose a novel method for detecting minutiae in fingerprint images using YOLOv5, a state-of-the-art object detection algorithm. Our approach utilizes a convolutional neural network (CNN) to identify and locate minutiae points, ...

Quantity and the quality of detected discriminating features is very important in any recognition system. In minutia based fingerprint matching techniques, the performance depends upon the quality and quantity of the detected genuine minutia ...

Traditional minutiae-based matching algorithms are challenged by the probability that minutiae from different regions of different fingers may not be well matched, and hence lead to erroneous matching results. In this paper we introduce a novel feature ...

This paper proposes a novel minutiae-based fingerprint matching algorithm. A fingerprint is represented by minutiae set and sampling points on all ridges. Therefore, the foreground of a fingerprint image can be accurately estimated by the sampling ...

Matching incomplete or partial fingerprints continues to be an important challenge today, despite the advances made in fingerprint identification techniques. While the introduction of compact silicon chip-based sensors that capture only part of the ...