Missing Data Reconstruction Using Gaussian Mixture Models for Fingerprint Images
نویسندگان
چکیده
One of the most important areas in fingerprint biometrics is matching partial fingerprints in fingerprint databases. Recently, significant progress has been made in designing fingerprint identification systems for missing fingerprint information. However, the precise reconstruction of fingerprint images still remains challenging due to the complexity and the ill-posed nature of the problem. This paper presents an algorithm for reconstructing the missing data from the fingerprint image(s). Experimental results illustrate the performance of the proposed method. The offered system can be used for fingerprint image identification and can be automated, as well as extended to numerous other security applications such as postmortem fingerprints, forensic science, investigations, artificial intelligence, robotics, all-access control, and financial security, as well as for the verification of firearm purchasers, driver license applicants, etc.
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