{"title":"一种新的ATR系统中视频模式识别的不变量集","authors":"I. Vizitiu, C. Molder, I.A. Radu, D. Munteanu","doi":"10.1109/OPTIM.2008.4602472","DOIUrl":null,"url":null,"abstract":"The choice of an appropriate feature extraction method is essential for the success of the classification or recognition process. T his paper proposes a design method for a new pattern descriptor set based on the Flusser moment class, which is invariant to elementary geometric transformations and has an increased robustness to the action of some perturbations. Experimental results based on the use of a real video image database confirm the basic properties of this new descriptor set.","PeriodicalId":244464,"journal":{"name":"2008 11th International Conference on Optimization of Electrical and Electronic Equipment","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new invariant set for video pattern recognition in ATR systems\",\"authors\":\"I. Vizitiu, C. Molder, I.A. Radu, D. Munteanu\",\"doi\":\"10.1109/OPTIM.2008.4602472\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The choice of an appropriate feature extraction method is essential for the success of the classification or recognition process. T his paper proposes a design method for a new pattern descriptor set based on the Flusser moment class, which is invariant to elementary geometric transformations and has an increased robustness to the action of some perturbations. Experimental results based on the use of a real video image database confirm the basic properties of this new descriptor set.\",\"PeriodicalId\":244464,\"journal\":{\"name\":\"2008 11th International Conference on Optimization of Electrical and Electronic Equipment\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 11th International Conference on Optimization of Electrical and Electronic Equipment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OPTIM.2008.4602472\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 11th International Conference on Optimization of Electrical and Electronic Equipment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OPTIM.2008.4602472","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new invariant set for video pattern recognition in ATR systems
The choice of an appropriate feature extraction method is essential for the success of the classification or recognition process. T his paper proposes a design method for a new pattern descriptor set based on the Flusser moment class, which is invariant to elementary geometric transformations and has an increased robustness to the action of some perturbations. Experimental results based on the use of a real video image database confirm the basic properties of this new descriptor set.