Narumol Chumuang, Sattarpoom Thaiparnit, M. Ketcham
{"title":"HSV颜色模型中叶面按度分离算法设计及线性回归估计叶面积","authors":"Narumol Chumuang, Sattarpoom Thaiparnit, M. Ketcham","doi":"10.1109/SITIS.2016.104","DOIUrl":null,"url":null,"abstract":"Plant leaves are very important for their respiration and photosynthesis. The two processes are significant factors for their growth. Measuring leave dimension is very important in studying and analyzing the photosynthesis of plants. Leaf dimension assessment with image evaluation is the most widely technique used for presenting. This paper proposed the algorithm of image segmentation to classify image elements and calculate leaf surface with a threshold segmentation technique by using the constant threshold in gray color model and calculating the degree of green color in the HSV models. Segmentation technique is used to separate good surface out of defective surface of leaf image. Moreover, this paper also proposed leaf area estimation with linear regression analysis with the pixel value on the leaf surface. Further to sixty experiments, they showed the accuracy to separate elements of good surface and defective surface are 98.72% and 96.47% respectively.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Algorithm Design in Leaf Surface Separation by Degree in HSV Color Model and Estimation of Leaf Area by Linear Regression\",\"authors\":\"Narumol Chumuang, Sattarpoom Thaiparnit, M. Ketcham\",\"doi\":\"10.1109/SITIS.2016.104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Plant leaves are very important for their respiration and photosynthesis. The two processes are significant factors for their growth. Measuring leave dimension is very important in studying and analyzing the photosynthesis of plants. Leaf dimension assessment with image evaluation is the most widely technique used for presenting. This paper proposed the algorithm of image segmentation to classify image elements and calculate leaf surface with a threshold segmentation technique by using the constant threshold in gray color model and calculating the degree of green color in the HSV models. Segmentation technique is used to separate good surface out of defective surface of leaf image. Moreover, this paper also proposed leaf area estimation with linear regression analysis with the pixel value on the leaf surface. Further to sixty experiments, they showed the accuracy to separate elements of good surface and defective surface are 98.72% and 96.47% respectively.\",\"PeriodicalId\":403704,\"journal\":{\"name\":\"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SITIS.2016.104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITIS.2016.104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Algorithm Design in Leaf Surface Separation by Degree in HSV Color Model and Estimation of Leaf Area by Linear Regression
Plant leaves are very important for their respiration and photosynthesis. The two processes are significant factors for their growth. Measuring leave dimension is very important in studying and analyzing the photosynthesis of plants. Leaf dimension assessment with image evaluation is the most widely technique used for presenting. This paper proposed the algorithm of image segmentation to classify image elements and calculate leaf surface with a threshold segmentation technique by using the constant threshold in gray color model and calculating the degree of green color in the HSV models. Segmentation technique is used to separate good surface out of defective surface of leaf image. Moreover, this paper also proposed leaf area estimation with linear regression analysis with the pixel value on the leaf surface. Further to sixty experiments, they showed the accuracy to separate elements of good surface and defective surface are 98.72% and 96.47% respectively.