{"title":"卫星图像中类别数量的简单估计","authors":"Kitti Koonsanit, C. Jaruskulchai","doi":"10.1109/ICTKE.2012.6152390","DOIUrl":null,"url":null,"abstract":"Clustering is a popular tool for exploratory data analysis, such as K-means and Fuzzy C-mean. A simple estimation the number of classes for segmented areas (K) in satellite imagery application is often needed in advance as an input parameter to the K-means algorithm. In this paper, a method has been developed to estimate the number of classes for segmented areas in satellite imagery clustering application using an image processing technique based on the co-occurrence matrix technique. The proposed method was tested using data from known the number of classes with satellite imagery. The results from the tests confirm the effectiveness of the proposed method in finding the estimation the number of classes and compared with ground truth data.","PeriodicalId":235347,"journal":{"name":"2011 Ninth International Conference on ICT and Knowledge Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A simple estimation the number of classes in satellite imagery\",\"authors\":\"Kitti Koonsanit, C. Jaruskulchai\",\"doi\":\"10.1109/ICTKE.2012.6152390\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Clustering is a popular tool for exploratory data analysis, such as K-means and Fuzzy C-mean. A simple estimation the number of classes for segmented areas (K) in satellite imagery application is often needed in advance as an input parameter to the K-means algorithm. In this paper, a method has been developed to estimate the number of classes for segmented areas in satellite imagery clustering application using an image processing technique based on the co-occurrence matrix technique. The proposed method was tested using data from known the number of classes with satellite imagery. The results from the tests confirm the effectiveness of the proposed method in finding the estimation the number of classes and compared with ground truth data.\",\"PeriodicalId\":235347,\"journal\":{\"name\":\"2011 Ninth International Conference on ICT and Knowledge Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-02-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Ninth International Conference on ICT and Knowledge Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTKE.2012.6152390\",\"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 Ninth International Conference on ICT and Knowledge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTKE.2012.6152390","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A simple estimation the number of classes in satellite imagery
Clustering is a popular tool for exploratory data analysis, such as K-means and Fuzzy C-mean. A simple estimation the number of classes for segmented areas (K) in satellite imagery application is often needed in advance as an input parameter to the K-means algorithm. In this paper, a method has been developed to estimate the number of classes for segmented areas in satellite imagery clustering application using an image processing technique based on the co-occurrence matrix technique. The proposed method was tested using data from known the number of classes with satellite imagery. The results from the tests confirm the effectiveness of the proposed method in finding the estimation the number of classes and compared with ground truth data.