A novel cancelable finger vein templates based on LDM and RetinexGan

•We propose herein, a new cancelable biometric scheme based on Local Dissimilarity Map and RetinexGAN model, in order to address the issue of template protection.•An efficient way for finger vein features representation, which investigates the relationships and correlation inter and intra classes, while effectively coming up with the accidental shifts/rotations caused by the arbitrary position of the finger during image acquisition, is presented in this work.•An efficient way to deal with low light image enhancement purposes based on Retinex theory and Generative Adversarial Network(GAN), is proposed in this paper.•An efficient way to establish the best compromise between workload reduction and biometric template protection is proposed in this paper. In this paper, we propose a new biometric template protection scheme, which can deal with the finger vein biometric security threats, through using the LDM and RetinexGAN model. The RetinexGAN model is mainly used to handle the illumination and low contrast problems effectively, while efficiently extracting discriminative features from the finger vein images. The projection of extracted features into dissimilarity space is done using Local Dissimilarity Map (LDM). LDM is an efficient way for finger vein features representation, which investigates the relationships and correlation inter and intra classes, while effectively coming up with the accidental shifts/rotations caused by the arbitrary position of the finger during image acquisition. The proposed approach is successfully evaluated in terms of non-invertibility, non-linkability, revocability and performances. Experimental results and comparison analysis with the state of arts methods confirm that the proposed framework can achieve promising results.