Johannes Schuiki, Christof Kauba, H. Hofbauer, A. Uhl
{"title":"跨传感器微纹理材料分类和智能手机采集不能很好地结合在一起","authors":"Johannes Schuiki, Christof Kauba, H. Hofbauer, A. Uhl","doi":"10.1109/IWBF57495.2023.10157739","DOIUrl":null,"url":null,"abstract":"Intrinsic, non-invasive product authentication is still an important topic as it does not generate additional costs during the production process. This topic is of specific interest for medical products as non-genuine products can directly effect the patients’ health. This work investigates micro-texture classification as a mean of proving the authenticity of zircon oxide blocks (for dental implants). Samples of three different manufacturers were acquired using four smartphone devices with a clip-on macro lens. In addition, an existing drug packaging material database was utilized. While the intra-sensor microtexture classification worked well, the cross-sensor classification results were less promising. In an attempt to track down the limiting factors, intrinsic sensor features usually used in device identification were investigated as well.","PeriodicalId":273412,"journal":{"name":"2023 11th International Workshop on Biometrics and Forensics (IWBF)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cross-Sensor Micro-Texture Material Classification and Smartphone Acquisition do not go well together\",\"authors\":\"Johannes Schuiki, Christof Kauba, H. Hofbauer, A. Uhl\",\"doi\":\"10.1109/IWBF57495.2023.10157739\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Intrinsic, non-invasive product authentication is still an important topic as it does not generate additional costs during the production process. This topic is of specific interest for medical products as non-genuine products can directly effect the patients’ health. This work investigates micro-texture classification as a mean of proving the authenticity of zircon oxide blocks (for dental implants). Samples of three different manufacturers were acquired using four smartphone devices with a clip-on macro lens. In addition, an existing drug packaging material database was utilized. While the intra-sensor microtexture classification worked well, the cross-sensor classification results were less promising. In an attempt to track down the limiting factors, intrinsic sensor features usually used in device identification were investigated as well.\",\"PeriodicalId\":273412,\"journal\":{\"name\":\"2023 11th International Workshop on Biometrics and Forensics (IWBF)\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 11th International Workshop on Biometrics and Forensics (IWBF)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWBF57495.2023.10157739\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 11th International Workshop on Biometrics and Forensics (IWBF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWBF57495.2023.10157739","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cross-Sensor Micro-Texture Material Classification and Smartphone Acquisition do not go well together
Intrinsic, non-invasive product authentication is still an important topic as it does not generate additional costs during the production process. This topic is of specific interest for medical products as non-genuine products can directly effect the patients’ health. This work investigates micro-texture classification as a mean of proving the authenticity of zircon oxide blocks (for dental implants). Samples of three different manufacturers were acquired using four smartphone devices with a clip-on macro lens. In addition, an existing drug packaging material database was utilized. While the intra-sensor microtexture classification worked well, the cross-sensor classification results were less promising. In an attempt to track down the limiting factors, intrinsic sensor features usually used in device identification were investigated as well.