Nguyen Van Binh, Trinh Phu Duy, Thi Thuy Nga Le, Nguyen Van Son
{"title":"基于图像处理的交通目标识别驾驶员分心快速预警系统","authors":"Nguyen Van Binh, Trinh Phu Duy, Thi Thuy Nga Le, Nguyen Van Son","doi":"10.1109/ATC55345.2022.9942980","DOIUrl":null,"url":null,"abstract":"Along with socio-economic development, the number of cars is increasing, which means more and more potential hazards on the road. These dangers come not only from the subjective behavior of the driver but also from objective incidents. Building an automated system to detect incidents in time plays an important role in reducing traffic accidents. This study proposes a fast image processing method to detect driver distractions to give timely warnings. In addition, the objects on the road that are at risk of causing an accident are also recognized and the system warns the driver in real time. Selected study results are also provided to verify the effectiveness of the method.","PeriodicalId":135827,"journal":{"name":"2022 International Conference on Advanced Technologies for Communications (ATC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast Warning System for Driver of Distraction with Traffic Object Recognition by Image Processing\",\"authors\":\"Nguyen Van Binh, Trinh Phu Duy, Thi Thuy Nga Le, Nguyen Van Son\",\"doi\":\"10.1109/ATC55345.2022.9942980\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Along with socio-economic development, the number of cars is increasing, which means more and more potential hazards on the road. These dangers come not only from the subjective behavior of the driver but also from objective incidents. Building an automated system to detect incidents in time plays an important role in reducing traffic accidents. This study proposes a fast image processing method to detect driver distractions to give timely warnings. In addition, the objects on the road that are at risk of causing an accident are also recognized and the system warns the driver in real time. Selected study results are also provided to verify the effectiveness of the method.\",\"PeriodicalId\":135827,\"journal\":{\"name\":\"2022 International Conference on Advanced Technologies for Communications (ATC)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Advanced Technologies for Communications (ATC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ATC55345.2022.9942980\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Advanced Technologies for Communications (ATC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATC55345.2022.9942980","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast Warning System for Driver of Distraction with Traffic Object Recognition by Image Processing
Along with socio-economic development, the number of cars is increasing, which means more and more potential hazards on the road. These dangers come not only from the subjective behavior of the driver but also from objective incidents. Building an automated system to detect incidents in time plays an important role in reducing traffic accidents. This study proposes a fast image processing method to detect driver distractions to give timely warnings. In addition, the objects on the road that are at risk of causing an accident are also recognized and the system warns the driver in real time. Selected study results are also provided to verify the effectiveness of the method.