{"title":"基于图像识别的花生荚原产地溯源研究","authors":"Han Zhongzhi, Deng Limiao, Yu Renshi","doi":"10.1109/ICSSEM.2011.6081338","DOIUrl":null,"url":null,"abstract":"In order to investigate variety-specific reflected by peanut from different origin, we use a scanner to capture the images of the same species (Huayu 22) from three different regions, Each variety includes one front and two side images of 100 peanuts respectively. For each image, we have acquired 50 characteristics including shape, color and texture characteristics. We built artificial neural network model for identification based on these characteristics and those optimized by PCA, Result shows that for different species origin the maximal detectable rate reaches 100%. Methods and conclusions of this paper have positive significance to the DUS testing of peanut.","PeriodicalId":406311,"journal":{"name":"2011 International Conference on System science, Engineering design and Manufacturing informatization","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study on origin traceability of peanut pods based on image recognition\",\"authors\":\"Han Zhongzhi, Deng Limiao, Yu Renshi\",\"doi\":\"10.1109/ICSSEM.2011.6081338\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to investigate variety-specific reflected by peanut from different origin, we use a scanner to capture the images of the same species (Huayu 22) from three different regions, Each variety includes one front and two side images of 100 peanuts respectively. For each image, we have acquired 50 characteristics including shape, color and texture characteristics. We built artificial neural network model for identification based on these characteristics and those optimized by PCA, Result shows that for different species origin the maximal detectable rate reaches 100%. Methods and conclusions of this paper have positive significance to the DUS testing of peanut.\",\"PeriodicalId\":406311,\"journal\":{\"name\":\"2011 International Conference on System science, Engineering design and Manufacturing informatization\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on System science, Engineering design and Manufacturing informatization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSEM.2011.6081338\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on System science, Engineering design and Manufacturing informatization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSEM.2011.6081338","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study on origin traceability of peanut pods based on image recognition
In order to investigate variety-specific reflected by peanut from different origin, we use a scanner to capture the images of the same species (Huayu 22) from three different regions, Each variety includes one front and two side images of 100 peanuts respectively. For each image, we have acquired 50 characteristics including shape, color and texture characteristics. We built artificial neural network model for identification based on these characteristics and those optimized by PCA, Result shows that for different species origin the maximal detectable rate reaches 100%. Methods and conclusions of this paper have positive significance to the DUS testing of peanut.