Kengo Makino, W. Duan, Rui Ishiyama, Toru Takahashi, Yuta Kudo, P. Jonker
{"title":"无标记或标签零件的自动扫描和单独识别系统","authors":"Kengo Makino, W. Duan, Rui Ishiyama, Toru Takahashi, Yuta Kudo, P. Jonker","doi":"10.1145/3206025.3206088","DOIUrl":null,"url":null,"abstract":"This paper presents a fully automated system for detecting, classifying, microscopic imaging, and individually identifying multiple parts without ID-marking or tagging. The system is beneficial for product assemblers, who handle multiple types of parts simultaneously. They can ensure traceability quite easily by only placing the parts freely on the system platform. The system captures microscopic images of parts as their \"fingerprints,\" which are matched with pre-registered images in a database to identify an individual part's information such as its serial number. We demonstrate a working prototype and interaction scenario.","PeriodicalId":224132,"journal":{"name":"Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automated Scanning and Individual Identification System for Parts without Marking or Tagging\",\"authors\":\"Kengo Makino, W. Duan, Rui Ishiyama, Toru Takahashi, Yuta Kudo, P. Jonker\",\"doi\":\"10.1145/3206025.3206088\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a fully automated system for detecting, classifying, microscopic imaging, and individually identifying multiple parts without ID-marking or tagging. The system is beneficial for product assemblers, who handle multiple types of parts simultaneously. They can ensure traceability quite easily by only placing the parts freely on the system platform. The system captures microscopic images of parts as their \\\"fingerprints,\\\" which are matched with pre-registered images in a database to identify an individual part's information such as its serial number. We demonstrate a working prototype and interaction scenario.\",\"PeriodicalId\":224132,\"journal\":{\"name\":\"Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3206025.3206088\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3206025.3206088","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automated Scanning and Individual Identification System for Parts without Marking or Tagging
This paper presents a fully automated system for detecting, classifying, microscopic imaging, and individually identifying multiple parts without ID-marking or tagging. The system is beneficial for product assemblers, who handle multiple types of parts simultaneously. They can ensure traceability quite easily by only placing the parts freely on the system platform. The system captures microscopic images of parts as their "fingerprints," which are matched with pre-registered images in a database to identify an individual part's information such as its serial number. We demonstrate a working prototype and interaction scenario.