{"title":"基于特征差异的彩色目标SSDA","authors":"Ligong Sun, Sujuan Li, Leiming Zhang, Fei Xiang","doi":"10.1109/ICCSEE.2012.387","DOIUrl":null,"url":null,"abstract":"The paper proposes a sequential similarity detection algorithm (SSDA) for colored target based on characteristic differences. It analyzes basic SSDA, combines the characteristics of color, shape and size, then improves the SSDA. Experimental results show that the improved SSDA reduces the computational complexity, improves target identification accuracy, with better real-time.","PeriodicalId":132465,"journal":{"name":"2012 International Conference on Computer Science and Electronics Engineering","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SSDA for Colored Target Based on Characteristic Differences\",\"authors\":\"Ligong Sun, Sujuan Li, Leiming Zhang, Fei Xiang\",\"doi\":\"10.1109/ICCSEE.2012.387\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper proposes a sequential similarity detection algorithm (SSDA) for colored target based on characteristic differences. It analyzes basic SSDA, combines the characteristics of color, shape and size, then improves the SSDA. Experimental results show that the improved SSDA reduces the computational complexity, improves target identification accuracy, with better real-time.\",\"PeriodicalId\":132465,\"journal\":{\"name\":\"2012 International Conference on Computer Science and Electronics Engineering\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Computer Science and Electronics Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSEE.2012.387\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Computer Science and Electronics Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSEE.2012.387","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SSDA for Colored Target Based on Characteristic Differences
The paper proposes a sequential similarity detection algorithm (SSDA) for colored target based on characteristic differences. It analyzes basic SSDA, combines the characteristics of color, shape and size, then improves the SSDA. Experimental results show that the improved SSDA reduces the computational complexity, improves target identification accuracy, with better real-time.
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