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Wavelet Coefficient Based Image Copy Detection and Privacy Preserving Using SIFT Attributes of Fingerprints

Recently, due to affordable price and easy operation on digital camera, large amount of digital images are available. In addition to that digital processing gives user privilege to modify the copy and spread the image over the internet. Digital multimedia, social networking and many more sites which deals with the images and that needs to be protected. To assure privacy of this storage there must be measures for copyright verification, image-content identification, copy detection, privacy and authentication perfectly. This architecture is proposed to solve the above problem of privacy of images. One way to solve it is to use the signs of Discrete Wavelet Transform (DWT) coefficients. The DWT based architecture allows searching images in the encrypted domain which is called as perceptual encryption. Sift attributes of fingerprints are used as input with the image to preserve privacy. The system will generates the set of two keys for scrambling of an image using sign component of low frequency wavelet coefficient which belongs to the particular image. Finally the statistical properties of these DWT sign vectors are modeled and focused on analyzing their robustness against real world image distortions. Keywords— copyright, Content Based Image Copy Detection, Redundancy, SIFT.