{"title":"利用认知方法从彩色图像中提取道路特征","authors":"C. Rotaru, T. Graf, Jianwei Zhang","doi":"10.1109/IVS.2004.1336398","DOIUrl":null,"url":null,"abstract":"This paper introduces a cognitive method for extracting significant road information (like road extents, lane markings) from mono-color images. The system is able to identify all traffic lanes and to distinguish between continuous and broken lane markings. Its output is useful in driver assistance systems (for example lane-departure warning). The cognitive aspects of the system are highlighted and the implemented algorithms are described. Finally, some results of the performed tests are introduced before drawing the conclusion.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":"{\"title\":\"Extracting road features from color images using a cognitive approach\",\"authors\":\"C. Rotaru, T. Graf, Jianwei Zhang\",\"doi\":\"10.1109/IVS.2004.1336398\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a cognitive method for extracting significant road information (like road extents, lane markings) from mono-color images. The system is able to identify all traffic lanes and to distinguish between continuous and broken lane markings. Its output is useful in driver assistance systems (for example lane-departure warning). The cognitive aspects of the system are highlighted and the implemented algorithms are described. Finally, some results of the performed tests are introduced before drawing the conclusion.\",\"PeriodicalId\":296386,\"journal\":{\"name\":\"IEEE Intelligent Vehicles Symposium, 2004\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"36\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Intelligent Vehicles Symposium, 2004\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2004.1336398\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Intelligent Vehicles Symposium, 2004","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2004.1336398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extracting road features from color images using a cognitive approach
This paper introduces a cognitive method for extracting significant road information (like road extents, lane markings) from mono-color images. The system is able to identify all traffic lanes and to distinguish between continuous and broken lane markings. Its output is useful in driver assistance systems (for example lane-departure warning). The cognitive aspects of the system are highlighted and the implemented algorithms are described. Finally, some results of the performed tests are introduced before drawing the conclusion.
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