{"title":"基于人工蜂群算法优化的直觉模糊集局部对比度增强","authors":"D. M. Wonohadidjojo","doi":"10.21512/COMTECH.V8I1.3777","DOIUrl":null,"url":null,"abstract":"The article presented the enhancement method of cells images. The first method used in the local contrast enhancement was Intuitionistic Fuzzy Sets (IFS). The proposed method is the IFS optimized by Artificial Bee Colony (ABC) algorithm. The ABC was used to optimize the membership function parameter of IFS. To measure the image quality, Image Enhancement Metric (IEM) was applied. The results of local contrast enhancement using both methods were compared with the results using histogram equalization method. The tests were conducted using two MDCK cell images. The results of local contrast enhancement using both methods were evaluated by observing the enhanced images and IEM values. The results show that the methods outperform the histogram equalization method. Furthermore, the method using IFSABC is better than the IFS method.","PeriodicalId":31095,"journal":{"name":"ComTech","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Local Contrast Enhancement Using Intuitionistic Fuzzy Sets Optimized By Artificial Bee Colony Algorithm\",\"authors\":\"D. M. Wonohadidjojo\",\"doi\":\"10.21512/COMTECH.V8I1.3777\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article presented the enhancement method of cells images. The first method used in the local contrast enhancement was Intuitionistic Fuzzy Sets (IFS). The proposed method is the IFS optimized by Artificial Bee Colony (ABC) algorithm. The ABC was used to optimize the membership function parameter of IFS. To measure the image quality, Image Enhancement Metric (IEM) was applied. The results of local contrast enhancement using both methods were compared with the results using histogram equalization method. The tests were conducted using two MDCK cell images. The results of local contrast enhancement using both methods were evaluated by observing the enhanced images and IEM values. The results show that the methods outperform the histogram equalization method. Furthermore, the method using IFSABC is better than the IFS method.\",\"PeriodicalId\":31095,\"journal\":{\"name\":\"ComTech\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ComTech\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21512/COMTECH.V8I1.3777\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ComTech","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21512/COMTECH.V8I1.3777","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Local Contrast Enhancement Using Intuitionistic Fuzzy Sets Optimized By Artificial Bee Colony Algorithm
The article presented the enhancement method of cells images. The first method used in the local contrast enhancement was Intuitionistic Fuzzy Sets (IFS). The proposed method is the IFS optimized by Artificial Bee Colony (ABC) algorithm. The ABC was used to optimize the membership function parameter of IFS. To measure the image quality, Image Enhancement Metric (IEM) was applied. The results of local contrast enhancement using both methods were compared with the results using histogram equalization method. The tests were conducted using two MDCK cell images. The results of local contrast enhancement using both methods were evaluated by observing the enhanced images and IEM values. The results show that the methods outperform the histogram equalization method. Furthermore, the method using IFSABC is better than the IFS method.