A hybrid fingerprint identification system for immigration control using the Minutiae and correlation methods

Abstract

A growing security issue today in Nigeria is the increased occurrence of identity fraud. Research tends to show that perpetrators of this act are foreigners who enter the country without any document and are employed as security officers, thereby posing security treats to lives and properties. These foreigners device a means of beating security devices put in place at the border. The Nigerian Immigration uses Automated Fingerprint Identification System (AFIS) which is minutiae-based and less noise tolerant unlike the correlation-based approach. This paper therefore proposes a novel fingerprinting method that can help identify identity fraud. The method combines two approaches, namely minutiae and correlation approaches. The two approaches use extraction and matching to get good and reliable images. The idea is to see how the shortcomings of one are complemented by the other. Each of the approaches computes the matching score, and the mean of the two resulting scores is taken. The mean is compared with the established threshold such that the system provides response by indicating whether the verification is successful or not. It follows that the adoption of this new method by organizations like the Nigerian Immigration Service will drastically reduce, if not totally eradicate, the level of insecurity in the country

Keywords: Fingerprint Identification System, Security, Immigration Control,  Minutiae Method, Correlation Method, Identity fraud