Fingerprint verification using correlation filters
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Adaptive context-aware filter fusion for face recognition on bad illumination
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
On the filter combination for efficient image preprocessing under uneven illumination
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Hybrid filter fusion for robust visual information processing
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
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In this paper we propose reduced memory biometric filters for performing distortion tolerant face authentication. The focus of this research is on implementing authentication algorithms on small factor devices with limited memory and computational resources. We compare the full complexity minimum average correlation energy filters for performing illumination tolerant face authentication with our proposed quad phase minimum average correlation energy filters[1] utilizing a Four-Level correlator. The proposed scheme requires only 2bits/frequency in the frequency domain achieving a compression ratio of up to 32:1 for each biometric filter while still attaining very good verification performance (100% in some cases). The results we show are based on the illumination subsets of the CMU PIE database[2] on 65 people with 21 facial images per person.