W. Mustafa, R. Santiagoo, Irfan Jamaluddin, N. S. Othman, W. Khairunizam, M. Rohani
{"title":"疟疾细胞图像检测方法的比较","authors":"W. Mustafa, R. Santiagoo, Irfan Jamaluddin, N. S. Othman, W. Khairunizam, M. Rohani","doi":"10.1109/ICASSDA.2018.8477624","DOIUrl":null,"url":null,"abstract":"In the image analysis process, thresholding is one of the most important preprocessing steps. Thresholding is a sort of picture division that separates protest apportioning a picture into a closer view and foundation. This project will describe a few selected thresholding methods such as Fuzzy C-Mean Algorithm's method, Wolf's method, Bradley's method, Bernsen's method, Triangle's Method and Deghost's Method. Each method will experiment with the malaria image. The objective of thresholding method is to simplify an image into something that is easier to examine. By using MATLAB R2017b as its core programming software, the image will be separated by unused background with uncertainty. The thresholding method will undergo image quality analysis such as Sensitivity and Specificity. Based on numerical anaylsis the Fuzzy C-Mean Algorithm method is more effective and good performance compared to the other methods.","PeriodicalId":185167,"journal":{"name":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Comparison of Detection Method on Malaria Cell Images\",\"authors\":\"W. Mustafa, R. Santiagoo, Irfan Jamaluddin, N. S. Othman, W. Khairunizam, M. Rohani\",\"doi\":\"10.1109/ICASSDA.2018.8477624\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the image analysis process, thresholding is one of the most important preprocessing steps. Thresholding is a sort of picture division that separates protest apportioning a picture into a closer view and foundation. This project will describe a few selected thresholding methods such as Fuzzy C-Mean Algorithm's method, Wolf's method, Bradley's method, Bernsen's method, Triangle's Method and Deghost's Method. Each method will experiment with the malaria image. The objective of thresholding method is to simplify an image into something that is easier to examine. By using MATLAB R2017b as its core programming software, the image will be separated by unused background with uncertainty. The thresholding method will undergo image quality analysis such as Sensitivity and Specificity. Based on numerical anaylsis the Fuzzy C-Mean Algorithm method is more effective and good performance compared to the other methods.\",\"PeriodicalId\":185167,\"journal\":{\"name\":\"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSDA.2018.8477624\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSDA.2018.8477624","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of Detection Method on Malaria Cell Images
In the image analysis process, thresholding is one of the most important preprocessing steps. Thresholding is a sort of picture division that separates protest apportioning a picture into a closer view and foundation. This project will describe a few selected thresholding methods such as Fuzzy C-Mean Algorithm's method, Wolf's method, Bradley's method, Bernsen's method, Triangle's Method and Deghost's Method. Each method will experiment with the malaria image. The objective of thresholding method is to simplify an image into something that is easier to examine. By using MATLAB R2017b as its core programming software, the image will be separated by unused background with uncertainty. The thresholding method will undergo image quality analysis such as Sensitivity and Specificity. Based on numerical anaylsis the Fuzzy C-Mean Algorithm method is more effective and good performance compared to the other methods.