{"title":"基于云计算的彩色图像分割质量控制方法研究","authors":"Jia Wang","doi":"10.1109/DSA.2019.00034","DOIUrl":null,"url":null,"abstract":"Traditional color image segmentation quality control method image segmentation quality is low, the control effect is not good. To solve the above problems, a color image segmentation quality control method based on cloud computing is proposed. This method is composed of five steps: first, color image acquisition architecture is designed, color image storage is completed by using cloud computing, th en cloud image is used to preprocess the collected image (color quantization, color space conversion, color similarity measurement), and th en cloud computing is used for color clustering. Finally, the regions are merged and deleted to achieve color image color consistency control and realize segmentation quality control. The results show that the method can effectively control the quality of color image segmentation, and the consistency, contrast and shape parameters are improved by 0.14, 0.19 and 0.19, respectively(Abstract).","PeriodicalId":342719,"journal":{"name":"2019 6th International Conference on Dependable Systems and Their Applications (DSA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Quality Control Method of Color Image Segmentation Based on Cloud Computing\",\"authors\":\"Jia Wang\",\"doi\":\"10.1109/DSA.2019.00034\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional color image segmentation quality control method image segmentation quality is low, the control effect is not good. To solve the above problems, a color image segmentation quality control method based on cloud computing is proposed. This method is composed of five steps: first, color image acquisition architecture is designed, color image storage is completed by using cloud computing, th en cloud image is used to preprocess the collected image (color quantization, color space conversion, color similarity measurement), and th en cloud computing is used for color clustering. Finally, the regions are merged and deleted to achieve color image color consistency control and realize segmentation quality control. The results show that the method can effectively control the quality of color image segmentation, and the consistency, contrast and shape parameters are improved by 0.14, 0.19 and 0.19, respectively(Abstract).\",\"PeriodicalId\":342719,\"journal\":{\"name\":\"2019 6th International Conference on Dependable Systems and Their Applications (DSA)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 6th International Conference on Dependable Systems and Their Applications (DSA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DSA.2019.00034\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 6th International Conference on Dependable Systems and Their Applications (DSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSA.2019.00034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Quality Control Method of Color Image Segmentation Based on Cloud Computing
Traditional color image segmentation quality control method image segmentation quality is low, the control effect is not good. To solve the above problems, a color image segmentation quality control method based on cloud computing is proposed. This method is composed of five steps: first, color image acquisition architecture is designed, color image storage is completed by using cloud computing, th en cloud image is used to preprocess the collected image (color quantization, color space conversion, color similarity measurement), and th en cloud computing is used for color clustering. Finally, the regions are merged and deleted to achieve color image color consistency control and realize segmentation quality control. The results show that the method can effectively control the quality of color image segmentation, and the consistency, contrast and shape parameters are improved by 0.14, 0.19 and 0.19, respectively(Abstract).