Class-Distribution Preserving Transform for Face Biometric Data Security
Y C Feng, Pong Chi Yuen · 2007
This paper addresses the face data variations problem in biometric cryptosystems in which the cryptographic technique is applied to biometric system. To overcome the limitation, this paper introduce a new class-distribution preserving transform to biometric cryptosystems. The basic idea is to transform a real value face feature vector to a binary feature vector using a random points set. The proposed transform is integrated into a BCH coding technique. Fisherface algorithm is used for feature extraction and ORL face database is selected for experiments. It is shown that only around 0.8% accuracy is degraded in comparing with the original Fisherface algorithm while the system security can be enhanced by 126 bits.