{"title":"利用方向场分离被遮挡的叶片","authors":"Nicha Piemkaroonwong, U. Watchareeruetai","doi":"10.1109/JCSSE.2017.8025929","DOIUrl":null,"url":null,"abstract":"This paper proposes a method that separates the region of each leaf from an image of occluded leaves and produces a set of single-leaf images as an output. To identify the region of a single leaf, intersection points and direction field are required. An intersection point, which is defined as a concave point between leaves, is used as the starting position of leaf estimation process. Direction field, which describes the average direction of edges in a local area, is used to guide the estimation process. Leaf separation process applies the result of leaf estimation process to create an output. Experimental results show that 71.23% of testing leaf images were correctly separated from each other with a segmentation accuracy of 88.80%.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"143 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Separation of occluded leaves using direction field\",\"authors\":\"Nicha Piemkaroonwong, U. Watchareeruetai\",\"doi\":\"10.1109/JCSSE.2017.8025929\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a method that separates the region of each leaf from an image of occluded leaves and produces a set of single-leaf images as an output. To identify the region of a single leaf, intersection points and direction field are required. An intersection point, which is defined as a concave point between leaves, is used as the starting position of leaf estimation process. Direction field, which describes the average direction of edges in a local area, is used to guide the estimation process. Leaf separation process applies the result of leaf estimation process to create an output. Experimental results show that 71.23% of testing leaf images were correctly separated from each other with a segmentation accuracy of 88.80%.\",\"PeriodicalId\":6460,\"journal\":{\"name\":\"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)\",\"volume\":\"143 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/JCSSE.2017.8025929\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/JCSSE.2017.8025929","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Separation of occluded leaves using direction field
This paper proposes a method that separates the region of each leaf from an image of occluded leaves and produces a set of single-leaf images as an output. To identify the region of a single leaf, intersection points and direction field are required. An intersection point, which is defined as a concave point between leaves, is used as the starting position of leaf estimation process. Direction field, which describes the average direction of edges in a local area, is used to guide the estimation process. Leaf separation process applies the result of leaf estimation process to create an output. Experimental results show that 71.23% of testing leaf images were correctly separated from each other with a segmentation accuracy of 88.80%.