Johannes Schuiki, Christof Kauba, H. Hofbauer, A. Uhl
{"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}
引用次数: 0
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.