Invariant Digital Image Watermarking Using Adaptive Harris Corner Detector

A robust and geometric invariant digital image watermarking scheme based on feature extraction and histogram distribution is proposed in this paper. The feature extraction method called Harris Corner Detector is adopted and revised by adjusting the response threshold value and ranking the response R value to extract feature points and thus define the regions for watermark data bits embedding and extraction. Each embedding region is a square matrix centering at the selected feature points. For watermark embedding, some pixels are moved to form a specific pattern in the intensity-level histogram distribution in each embedding region, indicating the watermark. For watermark extraction, the Adaptive Harris Corner Detector is adopted to restore the image to its original un-rotated position. According to the intensity-level histogram distribution in each embedded region, the watermark is extracted. Experimental results show that the proposed scheme is very robust against rotation, scaling, JPEG compression, median filtering, low-pass Gaussian filtering and also noise pollution.