Fingerprint Quality Check

Fingerprint quality check is a feature that is used to evaluate the quality of fingerprints captured by a fingerprint scanner & device camera, and determine whether they are suitable for use in authentication or identification processes. This feature can be used to improve the accuracy and reliability of fingerprint-based systems, and can be especially useful in scenarios where the fingerprints are of poor quality, due to factors such as dry skin, dirt, or other contaminants.

How it works:

Fingerprint quality check typically uses a combination of image processing and machine learning algorithms to analyze the fingerprints captured by the scanner. The algorithms analyze various features of the fingerprints such as the sharpness of the edges, the presence of ridges and valleys, and the overall contrast. The system then generates a quality score, indicating the level of confidence that the fingerprints are suitable for use.

How to use it:

To use the fingerprint quality check feature, you will need to have a fingerprint scanner and the software that performs the quality check. The user will need to place their finger on the scanner, and the software will then analyze the fingerprint image and generate a quality score. Depending on the specific implementation, the system may also have a user interface that allows you to review the quality check and make a final decision.

Benefits of Fingerprint Quality Check

Meet Regulatory Compliance

By evaluating the quality of fingerprints before using them for authentication or identification, you can ensure that the fingerprints are suitable for use, which can help to improve the overall accuracy of the system.

Convenience

Fingerprint quality check eliminates the need for manual inspection of fingerprints, which can save time and reduce errors.

Automation

Fingerprint quality check can be integrated into automated systems such as access control, e-commerce, and online transactions, which can improve the user experience and reduce the need for human intervention.

Explanation

Metrics	Explanation	Camera Images \| Good	Camera Images \| Bad	Scanned Images \| Good	Scanned Images \| Bad
Number of Quality blocks (Area covered by the fingerprint)	The number of grid cells which shows the area where the print itself covers in the image and be used for quality assessment.	82%	57%	72%	100%
Good blocks	The number of grid cells, that shows the good part of the fingerprint image	91%	43%	88%	N/A
Dark blocks	This is a percentage of the bad blocks out of the total number of quality blocks that appears to be too dark	0%	11%	0%	7%