{"title":"一种保持轮廓一致颜色的图像聚类技术","authors":"Sheng-Chih Yang, Shih-Yen Huang, Xi Liu","doi":"10.1109/IS3C.2014.39","DOIUrl":null,"url":null,"abstract":"While the image was sewed in cloth with thread or was made a physical model by 3D printer, the colors of the thread or the material of the 3D printer was limit, to simplify the manufacture processing. Although the conventional image clustering algorithm can segment the image into seldom clusters and give each cluster a specific color that decrease most colors and preserver the main feature. However the contour will be cluster in many clusters induce by the color gradient of the contour. This paper proposed a clustering algorithm based on involved spatial distance to assign the contour a consistent color. The experimental shown that the proposed algorithm had cluster quality more than 90%, the maximum improvement was 57% that compared with the conventional clustering algorithm.","PeriodicalId":149730,"journal":{"name":"2014 International Symposium on Computer, Consumer and Control","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Image Clustering Technology for Preserving the Consistent Color of Contour\",\"authors\":\"Sheng-Chih Yang, Shih-Yen Huang, Xi Liu\",\"doi\":\"10.1109/IS3C.2014.39\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While the image was sewed in cloth with thread or was made a physical model by 3D printer, the colors of the thread or the material of the 3D printer was limit, to simplify the manufacture processing. Although the conventional image clustering algorithm can segment the image into seldom clusters and give each cluster a specific color that decrease most colors and preserver the main feature. However the contour will be cluster in many clusters induce by the color gradient of the contour. This paper proposed a clustering algorithm based on involved spatial distance to assign the contour a consistent color. The experimental shown that the proposed algorithm had cluster quality more than 90%, the maximum improvement was 57% that compared with the conventional clustering algorithm.\",\"PeriodicalId\":149730,\"journal\":{\"name\":\"2014 International Symposium on Computer, Consumer and Control\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Symposium on Computer, Consumer and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IS3C.2014.39\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Symposium on Computer, Consumer and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IS3C.2014.39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Image Clustering Technology for Preserving the Consistent Color of Contour
While the image was sewed in cloth with thread or was made a physical model by 3D printer, the colors of the thread or the material of the 3D printer was limit, to simplify the manufacture processing. Although the conventional image clustering algorithm can segment the image into seldom clusters and give each cluster a specific color that decrease most colors and preserver the main feature. However the contour will be cluster in many clusters induce by the color gradient of the contour. This paper proposed a clustering algorithm based on involved spatial distance to assign the contour a consistent color. The experimental shown that the proposed algorithm had cluster quality more than 90%, the maximum improvement was 57% that compared with the conventional clustering algorithm.