An image copyright protection and tampering detection scheme based on deep learningand memristor

Authors:

Changjiu Pu, Chongqing University of Education, Chongqing, China

Fei Hu, Chongqing University of Education, Chongqing, China

Jie Long, Chongqing University of Education, Chongqing, China

Abstract:

Purpose. In order to improve the effect of image copyright protection and detect whether an image is tampered illegally, we introduce an image copyright protection and tampering detection scheme of ROI (Region of interest) image based on image feature sequence in NROI (Non Region of interest) image. We have evaluated this scheme with some performance measures and the results show it is effective.

Methodology. We formulate the scheme using the copyright watermarking and the fragile watermarking. With the deep learning, memristor chaos, Arnold transform and extend zigzag transform, the watermarkings are generated and embedded into ROI image in DCT (Discrete cosine transform) domain using the feature sequence of NROI image.

Findings. We first completed the division of ROI and NROI image and get the feature sequence of NROI image using deep learning and memristor chaos. Then by using the sequence and some methods such as Arnold transform, we obtained the scrambling copyright watermarking and the new fragile watermarking of each image grouping and embedded them into ROI image.

Originality. We realize the extraction of image feature sequence in NROI image using deep learning and memristor chaos. It is applied to generate and embed the scrambling copyright watermarking and the new fragile watermarking into ROI image. The research on this aspect has not been found at present.

Practical value. We have completed some validation experiments with some performance measures. The results show it can completely satisfy the need of secure transmission. This scheme features strong robustness and security.

References/Список літератури

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2016-11-15  579.39 KB  749