{"title":"一种基于群体智能的自动目标检测后处理算法","authors":"Chen Zhuo, Liu Xiangshuang, Zhu Xiaodong","doi":"10.1109/SNPD.2007.142","DOIUrl":null,"url":null,"abstract":"Presently, most target detection post-processing algorithms are short of self-adapting, which make them have many limitations in automatic target detection from the digital images. Therefore this paper provides a new type of automatic target detection post-processing algorithm (CASI) which adopts clustering algorithm based on swarm intelligence to post-process the detected target pixels. Because of the characteristics of self-organization, robustness, expandability and simplicity, CASI can self-adaptively restore the target pixels, divide them into different targets and delete the false alarm targets. Experimental results conform that the target detection post-processing effect of this new type of algorithm is much better than the ones of morphological transformation in common use.","PeriodicalId":197058,"journal":{"name":"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"An Automatic Target Detection Post-Processing Algorithm Based on Swarm Intelligence\",\"authors\":\"Chen Zhuo, Liu Xiangshuang, Zhu Xiaodong\",\"doi\":\"10.1109/SNPD.2007.142\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Presently, most target detection post-processing algorithms are short of self-adapting, which make them have many limitations in automatic target detection from the digital images. Therefore this paper provides a new type of automatic target detection post-processing algorithm (CASI) which adopts clustering algorithm based on swarm intelligence to post-process the detected target pixels. Because of the characteristics of self-organization, robustness, expandability and simplicity, CASI can self-adaptively restore the target pixels, divide them into different targets and delete the false alarm targets. Experimental results conform that the target detection post-processing effect of this new type of algorithm is much better than the ones of morphological transformation in common use.\",\"PeriodicalId\":197058,\"journal\":{\"name\":\"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SNPD.2007.142\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2007.142","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Automatic Target Detection Post-Processing Algorithm Based on Swarm Intelligence
Presently, most target detection post-processing algorithms are short of self-adapting, which make them have many limitations in automatic target detection from the digital images. Therefore this paper provides a new type of automatic target detection post-processing algorithm (CASI) which adopts clustering algorithm based on swarm intelligence to post-process the detected target pixels. Because of the characteristics of self-organization, robustness, expandability and simplicity, CASI can self-adaptively restore the target pixels, divide them into different targets and delete the false alarm targets. Experimental results conform that the target detection post-processing effect of this new type of algorithm is much better than the ones of morphological transformation in common use.