Biometric watermarks based on face recognition methods for authentication of digital images

Abstract

Because making digital images secure runs into the substantial challenge of owner authentication, many security schemes based on cryptography, steganography and watermarking technology include biometric recognition methods. To follow on these studies, this paper describes a combination of facial images with watermarking technology to automatically authenticate digital images owners/users. In the proposed methodology, biometric face recognition methods such as principal component analysis and eigenfeature regularization and extraction produce vectorial representations of facial images. These vectors are used as copyright watermarks, in a few common watermarking schemes, and are tested for identification purposes after they are extracted. Initially, watermarking algorithms are studied with some arbitrary cover image, and also the most robust algorithm is tested for different cover images of particular subjects. The strength of this paper is finding relationships between the original and extracted biometric data using neural networks instead of the most common, simple measures such as correlation coefficients or distance metrics. The NN subject identification is performed directly, as there is no need to reconstruct facial images after the watermarks are extracted, compute templates for particular subjects, or seek a suitable distance metric. What is more, the presented study includes a performance comparison of two machine learning methods, frequently used for face recognition, and of a few popular watermarking algorithms. Very promising identification results were obtained in many considered experiments, even those involving attacks on watermarked images. and watermarking [7,[15][16][17][18] are provided, because they now represent mainstream security technologies. This paper proposes a security model enabling the authentication of digital image owners using the watermarking

Maneuvering Digital Watermarking In Face Recognition

“…Multimedia copyright data are protected with this technology; also, the text files and databases are protected with the help of the digital watermarking technique. Two basic components are encompassed in a digital watermarking system, such as; the decoder and the encoder [20,21]. For combining a digital document with a watermark, for instance, in images watermarking, the requirements are an image, which is denoted as Co, a watermarking data contained watermark, which is indicated as 'W', an encoding algorithm, E for producing a watermarked image, indicated as CW and a security key, K. The signature and the cover document is taken by the encoder, and a watermarked image is created.…”

Biometric Watermarking Schemes Based on QR Decomposition and Schur Decompositon in RIDWT Domain

“…In the second set, biometric data is embedded into natural images to protect intellectual property rights and copyright. Various biometric data such as speech signal [10,11], fingerprint [12][13][14], face [15,16], iris [17][18][19][20], and signature [21] are used as watermark for this purpose. Authors in [18] and [19] embedded iris code into cover image using Discrete Wavelet Transform (DWT)-Singular Value Decomposition (SVD)-based and Discrete Cosine Transform (DCT)-SVD-based hybrid watermarking schemes, respectively.…”

Multi-Factor Authentication: A Survey

“…Finally, the advancement of this system reached the point of recognizing the actual expressions of the user [88]. To enable facial recognition, it is required to equip the system with at least one output device and a camera [89].…”