A biometric watermarking approach of fingerprint images by DLDA Gabor face features without altering minutiae

In this paper we propose a new approach for watermarking biometric fingerprint images using Gabor direct linear discriminant analysis face features. Our goal is to incorporate a watermark in the best embedding domain that preserves minutiae, which are the most relevant proven features of a fingerprint. We conducted a comprehensive study based on the influence of the watermark embedding domain choice on the performance of the minutiae-based identity and of the robustness and imperceptibility of the watermarking approach. Three embedding domains were tested: spatial, frequency and multiresolution. The various tests were performed on two biometric databases, multimodal and chimerical. The best results were recorded in the multiresolution domain in terms of preserving the minutiae number and positions. Moreover, this embedding domain led to the best verification performances and to a good compromise between robustness and imperceptibility.