Research on fast identification technology of forged fingerprints based on the improved K-means algorithm
by Zhao-ting Ren
International Journal of Biometrics (IJBM), Vol. 13, No. 1, 2021

Abstract: In order to overcome the low accuracy of the traditional method, a fast identification method based on the improved K-mean algorithm is proposed. Spatial grid block model is constructed to extract the fingerprint texture features and then the fingerprint profile features are detected using the edge outline extraction method. The Kalman fusion method is used to reconstruct fingerprint information. Using the neighbourhood distributed retrieval method, fingerprint image feature fusion is realised and the texture feature extraction model for forged fingerprints is established. The K-means clustering method is used for fingerprint feature clustering to realise fast identification of forged fingerprints. Experimental results show that the identification accuracy of this method is higher than 0.85, and the identification stability is good. The signal-to-noise ratio of fingerprint images is always between 25.3 dB and 82.3 dB, and the imaging quality is high, indicating that this method can realise fast and accurate identification of forged fingerprints.

Online publication date: Tue, 05-Jan-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biometrics (IJBM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email