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In artificial intelligence, any model that wants to achieve a good result isinseparable from a large number of high-quality data. It is especially true inthe field of tamper detection. This paper proposes a modified total variationnoise reduction method to acquire high-quality tampered images. Weautomatically crawl original and tampered images from the Baidu PS Bar. BaiduPS Bar is a website where net friends post countless tampered images.Subtracting the original image with the tampered image can highlight thetampered area. However, there is also substantial noise on the final print, sothese images can't be directly used in the deep learning model. Our modifiedtotal variation noise reduction method is aimed at solving this problem.Because a lot of text is slender, it is easy to lose text information after theopening and closing operation. We use MSER (Maximally Stable Extremal Regions)and NMS (Non-maximum Suppression) technology to extract text information. Andthen use the modified total variation noise reduction technology to process thesubtracted image. Finally, we can obtain an image with little noise by addingthe image and text information. And the idea also largely retains the textinformation. Datasets generated in this way can be used in deep learningmodels, and they will help the model achieve better results.

Manipulation Mask Generator: High-Quality Image Manipulation Mask Generation Method Based on Modified Total Variation Noise Reduction