{"title":"环境条件对PRNU的影响","authors":"Pucha Rohan, Priyanka Singh, M. Mohanty","doi":"10.1109/CSE53436.2021.00031","DOIUrl":null,"url":null,"abstract":"Photo Response Non-Uniformity (PRNU) has been used reliably in the field of digital forensics to identify the camera for multiple applications. Given its importance, we study how the different environmental conditions affect this unique camera property in this paper. We collected 18 different cameras and created a dataset by clicking photos of 10 different objects in the varied environmental conditions. To be specific, we clicked photos of objects in the sun, putting water droplets on the camera lens, placing objects inside water and, putting dust on the camera lens, apart from clicking the normal images of the objects in a closed room. To compute the PRNU of each of these 18 cameras, we clicked nearly 30 to 50 images of the plain surfaces. We then analyzed the behavior of these cameras, considering the computed PRNU as the baseline. We used the Peak to Correlation Energy (PCE) to evaluate a match for the camera. Here, we present the experimental results and the possible causes of failure for the PRNU for the specific cameras in varied environmental conditions.","PeriodicalId":6838,"journal":{"name":"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)","volume":"49 1","pages":"154-161"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effect of Environmental Conditions on PRNU\",\"authors\":\"Pucha Rohan, Priyanka Singh, M. Mohanty\",\"doi\":\"10.1109/CSE53436.2021.00031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Photo Response Non-Uniformity (PRNU) has been used reliably in the field of digital forensics to identify the camera for multiple applications. Given its importance, we study how the different environmental conditions affect this unique camera property in this paper. We collected 18 different cameras and created a dataset by clicking photos of 10 different objects in the varied environmental conditions. To be specific, we clicked photos of objects in the sun, putting water droplets on the camera lens, placing objects inside water and, putting dust on the camera lens, apart from clicking the normal images of the objects in a closed room. To compute the PRNU of each of these 18 cameras, we clicked nearly 30 to 50 images of the plain surfaces. We then analyzed the behavior of these cameras, considering the computed PRNU as the baseline. We used the Peak to Correlation Energy (PCE) to evaluate a match for the camera. Here, we present the experimental results and the possible causes of failure for the PRNU for the specific cameras in varied environmental conditions.\",\"PeriodicalId\":6838,\"journal\":{\"name\":\"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)\",\"volume\":\"49 1\",\"pages\":\"154-161\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSE53436.2021.00031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSE53436.2021.00031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Photo Response Non-Uniformity (PRNU) has been used reliably in the field of digital forensics to identify the camera for multiple applications. Given its importance, we study how the different environmental conditions affect this unique camera property in this paper. We collected 18 different cameras and created a dataset by clicking photos of 10 different objects in the varied environmental conditions. To be specific, we clicked photos of objects in the sun, putting water droplets on the camera lens, placing objects inside water and, putting dust on the camera lens, apart from clicking the normal images of the objects in a closed room. To compute the PRNU of each of these 18 cameras, we clicked nearly 30 to 50 images of the plain surfaces. We then analyzed the behavior of these cameras, considering the computed PRNU as the baseline. We used the Peak to Correlation Energy (PCE) to evaluate a match for the camera. Here, we present the experimental results and the possible causes of failure for the PRNU for the specific cameras in varied environmental conditions.