{"title":"用于计数大量对象流的图像处理硬件","authors":"P. Jonker, J. J. Gerbrands","doi":"10.1109/ICPR.1992.202124","DOIUrl":null,"url":null,"abstract":"A real-time pipelined image processing system operating in a time division multiplexing mode to serve up to 16 cameras, was realized to count the mass of a flow of bottles on a conveyor belt. The realized mass counting system proved to be a powerful tool capable of continuously counting bottles with a speed of approximately 500000 bottles a day per measurement point and with an accuracy of less then 0.5%.<<ETX>>","PeriodicalId":34917,"journal":{"name":"模式识别与人工智能","volume":"124 1","pages":"31-33"},"PeriodicalIF":0.0000,"publicationDate":"1992-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Image processing hardware for counting massive object streams\",\"authors\":\"P. Jonker, J. J. Gerbrands\",\"doi\":\"10.1109/ICPR.1992.202124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A real-time pipelined image processing system operating in a time division multiplexing mode to serve up to 16 cameras, was realized to count the mass of a flow of bottles on a conveyor belt. The realized mass counting system proved to be a powerful tool capable of continuously counting bottles with a speed of approximately 500000 bottles a day per measurement point and with an accuracy of less then 0.5%.<<ETX>>\",\"PeriodicalId\":34917,\"journal\":{\"name\":\"模式识别与人工智能\",\"volume\":\"124 1\",\"pages\":\"31-33\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"模式识别与人工智能\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.1992.202124\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"模式识别与人工智能","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/ICPR.1992.202124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
Image processing hardware for counting massive object streams
A real-time pipelined image processing system operating in a time division multiplexing mode to serve up to 16 cameras, was realized to count the mass of a flow of bottles on a conveyor belt. The realized mass counting system proved to be a powerful tool capable of continuously counting bottles with a speed of approximately 500000 bottles a day per measurement point and with an accuracy of less then 0.5%.<>