{"title":"揭示分子生物学实验图像上人为修饰的痕迹","authors":"H. Shao","doi":"10.1109/GlobalSIP.2018.8646594","DOIUrl":null,"url":null,"abstract":"There are always inaccurate image data, in a scientific paper, created by inappropriate post-processing operations. Hence, we propose in this paper a fast algorithm able to expose man-made invisible modifications on molecular-biological images. We designed an optimization equation to separate the approximated trend component from the input image. Then, we utilize the difference between the input and its approximated trend to bring out the discontinuities within the input image. We applied our method on a blind test image set and images extracted from papers that have been questioned by the public. The experiment results show that there indeed exist unnatural patterns on several screened images. Because screening for fabricated images on published papers is a sensitive topic, our MATLAB code will be released only after we present this paper at IEEE GlobalSIP 2018.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"UNVEILING VESTIGES OF MAN-MADE MODIFICATIONS ON MOLECULAR-BIOLOGICAL EXPERIMENT IMAGES\",\"authors\":\"H. Shao\",\"doi\":\"10.1109/GlobalSIP.2018.8646594\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are always inaccurate image data, in a scientific paper, created by inappropriate post-processing operations. Hence, we propose in this paper a fast algorithm able to expose man-made invisible modifications on molecular-biological images. We designed an optimization equation to separate the approximated trend component from the input image. Then, we utilize the difference between the input and its approximated trend to bring out the discontinuities within the input image. We applied our method on a blind test image set and images extracted from papers that have been questioned by the public. The experiment results show that there indeed exist unnatural patterns on several screened images. Because screening for fabricated images on published papers is a sensitive topic, our MATLAB code will be released only after we present this paper at IEEE GlobalSIP 2018.\",\"PeriodicalId\":119131,\"journal\":{\"name\":\"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GlobalSIP.2018.8646594\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobalSIP.2018.8646594","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
UNVEILING VESTIGES OF MAN-MADE MODIFICATIONS ON MOLECULAR-BIOLOGICAL EXPERIMENT IMAGES
There are always inaccurate image data, in a scientific paper, created by inappropriate post-processing operations. Hence, we propose in this paper a fast algorithm able to expose man-made invisible modifications on molecular-biological images. We designed an optimization equation to separate the approximated trend component from the input image. Then, we utilize the difference between the input and its approximated trend to bring out the discontinuities within the input image. We applied our method on a blind test image set and images extracted from papers that have been questioned by the public. The experiment results show that there indeed exist unnatural patterns on several screened images. Because screening for fabricated images on published papers is a sensitive topic, our MATLAB code will be released only after we present this paper at IEEE GlobalSIP 2018.
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