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An Efficient Fingerprint Identification Algorithm based on Minutiae and Invariant Moment
Mar 19, 2018Author:
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Title: An Efficient Fingerprint Identification Algorithm based on Minutiae and Invariant Moment

 Authors: Sang, J; Wang, HX; Qian, Q; Wu, HZ; Chen, Y

 Author Full Names: Sang, Jing; Wang, Hongxia; Qian, Qing; Wu, Hanzhou; Chen, Yi

 Source: PERSONAL AND UBIQUITOUS COMPUTING, 22 (1):71-80; SI 10.1007/s00779-017-1094-1 FEB 2018

 Language: English

 Abstract: While we are experiencing many advantages of digital technologies and products, the security issues are also attracting increasing concerns. The secure fingerprint identification has become one of the most important research topics because of these increasing concerns. It has promoted us to propose an efficient fingerprint identification algorithm based on minutiae and invariant moment in this paper. In the proposed algorithm, the raw fingerprint image is first enhanced by the short-time Fourier transform (STFT). After that, the fingerprint minutiae can be extracted, which thereafter are selected as the center of region of interest (ROI), according to morphological transformation. Finally, a metric called cosine similarity among invariant moments is utilized to judge the similarities between fingerprint objects in the procedure of identification. The proposed algorithm is not limited to the fingerprint image with the fingerprint core. Experimental results show that the proposed algorithm provides a better performance in terms of matching accuracy when compared with the related works. The average accuracy is up to 96.67%. Moreover, the use of invariant moment of the ROI can avoid the leakage of fingerprint information and improve the security level of fingerprint recognition. Therefore, the proposed scheme is potentially used in many applications, such as smart fingerprint lock, intelligent community management information system, and automation control of home appliances.

 ISSN: 1617-4909

 eISSN: 1617-4917

 IDS Number: FU4KC

 Unique ID: WOS:000423821000009

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