Abstract-This paper presents a novel image adaptive data hiding system using properties of the discrete wavelet transform and which is ready to use in combination with JPEG 2000. Image adaptive watermarking schemes determine the embedding samples and strength from the image statistics. We propose to use the energy of wavelet coefficients at high frequencies to measure the amount of distortion that can be tolerated by a lower frequency coefficient. The watermark decoder in image adaptive data hiding needs to estimate the same parameters used for encoding from a modified source and hence is vulnerable to desynchronization. We present a novel way to resolve these synchronization issues by employing specialized insertion, deletion and substitution codes. Given the low complexity and reduced perceptual impact of the embedding technique, it is suitable for inserting camera and/or projector information to facilitate image forensics.
Many passive image tamper detection techniques have been presented in the expanding field of image forensics. Some of these techniques use a classifier for a final decision based on whole image statistics, resulting in a lack of forgery localization. The aim of this paper is to add localization to a previously published algorithm that uses grey-level co-occurrence matrix (GLCM) for extracting texture features from the chromatic component of an image (Cb or Cr component). Experimental results show that we can localize tampering for different sized regions with reasonable accuracy. The main trade-off is a diminishing detection accuracy as the region size decreases.
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