Selective review of fingerprint enhancement, classification and matching techniques

Implementation of Fingerprint Sensors for Fingerprint Reader Prototypes Using a Microcontroller

“…'MurniSadar' English Course Pematangsiantar students usually attend by filling the attendance list book with signatures or placing a checkmark on the attendance list. Moreover, a tool was designed to make it easier to fill in the attendance list of existing students using a fingerprint sensor [27][28][29][30] using a microcontroller. This system was built by combining the tool with a web application to provide student attendance information that can be accessed via the internet.…”

Fingerprint image quality assessment based on BP neural network with hierarchical clustering

“…According to the way to improve the matching performance, FIQA methods can be divided into four categories: (i) for sample enrolment; (ii) for template update; (iii) for adaptive enhancement, i.e. the fingerprint image is enhanced according to the quality assessment result [13,14]; (iv) for minutiae quality assessment, which extracts reliable and efficient minutiae, and greatly improves the overall performance of the minutiae-based matching algorithm. When FIQA is used for minutiae quality assessment, the assessment results are often used to remove low-quality minutiae or to select high-quality minutiae as the best reference for all possible matching minutiae [15,16].…”