Multi-modal biological characteristic identification system based on iris and human face

Abstract

One system to identify the multi-mode biologic characteristic status bases on iris and person face. The biology character collection unit gathers pictures of iris and person face by two absolute gather channels and its collection sustaining flat roof makes users with different stature to input iris and person face pictures freely and cozily. The biology character identify unit uses picture disposing and Wavelet transform technology to get character template and to calculate the matching percent of iris characteristic template and mesh degree of person face character template, and get the final identify result by data fusion method. The biology character data bank storage the final inborn character template and congruence iris character template on person face character template to keep the privacy of biology character data and to increase the security of system. It combines biology character, mode identification, data amalgamation and computer technology to identify people figure with low error rate for iris identify and person face identify.

Description

Technical field: [0001] The invention belongs to the technical field of biometric feature recognition and pattern recognition, and in particular relates to a multimodal and non-contact identity recognition system combining two biometric features of iris and human face. Background technique: [0002] At present, some single biometric identification technologies, such as fingerprints, irises, faces, and hand shapes, have been put into practical applications in some special fields, and have shown great advantages in biometric identification; Reasons hinder the promotion of these new identification technologies. For example: fingerprint recognition, due to multiple collections, sweat and dust will form residues on the contact surface, resulting in the fingerprint image collected from the previous impact, which is one of the inherent shortcomings of contact collection. Existing fingerprint collectors, whether they are optical, capacitive or inductive, all have this problem. In ...

AI Technical Summary

Problems solved by technology

In addition, due to the shedding of the surface skin of some people, the collected fingerprints contain different broken lines, resulting in different pseudo-feature points, which makes the existing fingerprint recognition technology always have a certain error rate, although the absolute percentage figure Small, but considerable impact due to the large recognition base

The results of the 2004 International Fingerprint Verification Competition (FVC2004: Fingerprint Verification Competition, http: / / bias.csr.unibo.it / fvc2004) show that the current fingerprint recognition algorithm still has a 2% error rate

Another example is iris recognition, the invited paper of the 2004 International Conference on Pattern Recognition: Opportunities and Challenges Faced by Biometrics (Biometrics: A Grand Challenge, Proceedings of International Conference on Pattern Recognition, Cambridge, UK, Aug.2004) pointed out that although iris The recognition error rate is extremely low, and it is a non-contact biometric recognition, but because it has high requirements for the collected images, the existing collection equipment must set relatively harsh collection conditions, resulting in high Collection failure rate or registration failure rate, poor man-machine friendliness

Images