A watermarked image search method using compressed representation by a convolutional autoencoder
Kousuke Imamura, Kentaro Watanabe, Hideo Kuroda, Makoto Fujimura · 2021
Digital watermarking is the main method by which prevent illegal copying of proprietary images. In addition, to reduce the amount of damage caused by illegal distribution of proprietary images, a fast search technique for illegally distributed images on the Internet is necessary. We have proposed a two-stage search method for digital watermarked images. In the present paper, we propose a new high-efficiency pre-search algorithm for proprietary images that are suspected of being copied and distributed on the Internet. The proposed algorithm is capable of quickly identifying illegal copies from large image groups using mainly the correlation coefficient of compressed representations between the original image and a target image by convolutional autoencoder. The proposed search method has tolerance for attacks such as scaling, image compression, color reduction, and intensity conversion. The performance of the proposed search algorithm is evaluated through computer simulations.