Improved Face Image Authentication Scheme based on Embedding in Adjacent Coefficients

Abstract

Face image authentication (FIA) schemes have recently been developed using face detection and image watermarking technology. The research in this direction proved the presented schemes' efficiency in accurately detecting the manipulated face regions and recovering the original face region. Recovering the original face region is very important in practical applications. Still, it was at the cost of increasing the secret data that must be embedded in the face image. The increment in the secret data required a large embedding capacity, which was not available in some images. To overcome this limitation, an improved FIA scheme based on a new data embedding algorithm is presented in this paper. The suggested FIA scheme consists of two main algorithms applied at the sender and receiver sides, where both start by detecting the face region and dividing and classifying the image into blocks that belong to the face region or outside the face region. At the sender side, the secret data are generated from the face region and embedded in the blocks outside the face region using the suggested algorithm called Embedding in Adjacent Coefficients (EAC) for three subbands obtained after applying the Slantlet transform of the blocks. On the receiver side, the secret data are extracted from the blocks outside the face region using the suggested algorithm called Extraction from Adjacent Coefficients (ExAC). The extracted data is used to authenticate the face region and recover the original one when manipulations occur. The proposed FIA scheme obtained higher embedding capacity than previous ones, making it applicable to protect more face images that could not be protected using previous FIA schemes.