Takafumi Kawasaki, Takeshi Iwamoto, M. Matsumoto, Takuro Yonezawa, J. Nakazawa, K. Takashio, H. Tokuda
{"title":"A Method for Detecting Damage of Traffic Marks by Half Celestial Camera Attached to Cars","authors":"Takafumi Kawasaki, Takeshi Iwamoto, M. Matsumoto, Takuro Yonezawa, J. Nakazawa, K. Takashio, H. Tokuda","doi":"10.4108/eai.22-7-2015.2260306","DOIUrl":null,"url":null,"abstract":"Roads are becoming deterioration in everywhere. In some places, traffic marks painted on roads are damaged thus needed to be updated. Municipalities must manage road condition and traffic marks (road painting). It is the municipalities task to manage those roads using, for example, special inspection cars and human eyes. However, the management cost is high if a city contains many roads. This paper proposes a mechanism that automates this management. Our idea is to leverage cameras attached to garbage trucks, which run through the entire city almost everyday. The mechanism collects road images and detects damaged traffic marks using an image recognition algorithm. This paper shows the algorithm and reports the benchmark results. The benchmark showed that the mechanism can detect the damaged traffic marks with 76.6% precision.","PeriodicalId":334012,"journal":{"name":"EAI Endorsed Trans. Cogn. Commun.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EAI Endorsed Trans. Cogn. Commun.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/eai.22-7-2015.2260306","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Roads are becoming deterioration in everywhere. In some places, traffic marks painted on roads are damaged thus needed to be updated. Municipalities must manage road condition and traffic marks (road painting). It is the municipalities task to manage those roads using, for example, special inspection cars and human eyes. However, the management cost is high if a city contains many roads. This paper proposes a mechanism that automates this management. Our idea is to leverage cameras attached to garbage trucks, which run through the entire city almost everyday. The mechanism collects road images and detects damaged traffic marks using an image recognition algorithm. This paper shows the algorithm and reports the benchmark results. The benchmark showed that the mechanism can detect the damaged traffic marks with 76.6% precision.