Yuta Kudo, Hugo Zwaan, Toru Takahashi, Rui Ishiyama, P. Jonker
{"title":"Tip-on-a-chip: automatic dotting with glitter ink pen for individual identification of tiny parts","authors":"Yuta Kudo, Hugo Zwaan, Toru Takahashi, Rui Ishiyama, P. Jonker","doi":"10.1145/3204949.3208116","DOIUrl":null,"url":null,"abstract":"This paper presents a new identification system for tiny parts that have no space for applying conventional ID marking or tagging. The system marks the parts with a single dot using ink containing shiny particles. The particles in a single dot naturally form a unique pattern. The parts are then identified by matching microscopic images of this pattern with a database containing images of these dots. In this paper, we develop an automated system to conduct dotting and image capturing for mass-produced parts. Experimental results show that our \"Tip-on-a-chip\" system can uniquely identify more than ten thousand chip capacitors.","PeriodicalId":141196,"journal":{"name":"Proceedings of the 9th ACM Multimedia Systems Conference","volume":"37 7","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 9th ACM Multimedia Systems Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3204949.3208116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper presents a new identification system for tiny parts that have no space for applying conventional ID marking or tagging. The system marks the parts with a single dot using ink containing shiny particles. The particles in a single dot naturally form a unique pattern. The parts are then identified by matching microscopic images of this pattern with a database containing images of these dots. In this paper, we develop an automated system to conduct dotting and image capturing for mass-produced parts. Experimental results show that our "Tip-on-a-chip" system can uniquely identify more than ten thousand chip capacitors.