{"title":"面向路面违章检测的无人机图像分析","authors":"M. Kataev, Eugeny Kartashov, V. Avdeenko","doi":"10.1109/SIBCON56144.2022.10002994","DOIUrl":null,"url":null,"abstract":"Violations of the roadway leads to a decrease in the level of driver safety and the condition of the car, reduces the speed of movement. Violations include cracks, pits, ruts, the size of which can change every day, depending on weather conditions and traffic intensity. One of the well-known approaches for detecting violations of the roadway is technical vision and the entire set of image processing algorithms. The article considers a variant of solving the problem of detecting violations of the road surface from images obtained with the help of unmanned aerial vehicles. The approach is based on classical crack boundary detection algorithms and real images of the road are considered.","PeriodicalId":265523,"journal":{"name":"2022 International Siberian Conference on Control and Communications (SIBCON)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"UAV Image Analysis for Road Surface Violation Detection\",\"authors\":\"M. Kataev, Eugeny Kartashov, V. Avdeenko\",\"doi\":\"10.1109/SIBCON56144.2022.10002994\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Violations of the roadway leads to a decrease in the level of driver safety and the condition of the car, reduces the speed of movement. Violations include cracks, pits, ruts, the size of which can change every day, depending on weather conditions and traffic intensity. One of the well-known approaches for detecting violations of the roadway is technical vision and the entire set of image processing algorithms. The article considers a variant of solving the problem of detecting violations of the road surface from images obtained with the help of unmanned aerial vehicles. The approach is based on classical crack boundary detection algorithms and real images of the road are considered.\",\"PeriodicalId\":265523,\"journal\":{\"name\":\"2022 International Siberian Conference on Control and Communications (SIBCON)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Siberian Conference on Control and Communications (SIBCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIBCON56144.2022.10002994\",\"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 Siberian Conference on Control and Communications (SIBCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIBCON56144.2022.10002994","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
UAV Image Analysis for Road Surface Violation Detection
Violations of the roadway leads to a decrease in the level of driver safety and the condition of the car, reduces the speed of movement. Violations include cracks, pits, ruts, the size of which can change every day, depending on weather conditions and traffic intensity. One of the well-known approaches for detecting violations of the roadway is technical vision and the entire set of image processing algorithms. The article considers a variant of solving the problem of detecting violations of the road surface from images obtained with the help of unmanned aerial vehicles. The approach is based on classical crack boundary detection algorithms and real images of the road are considered.