{"title":"多车辆识别采用混合斑点分析和基于特征的方法","authors":"Anchisa Chantakamo, M. Ketcham","doi":"10.1109/ICITEED.2015.7408989","DOIUrl":null,"url":null,"abstract":"This paper presents an approach method to detect vehicle color and to classify multi vehicle from video data. The multi vehicle is classified by blob analysis and feature-based. The proposed method uses a video file recorded by traffic surveillance camera as input. This technique applied RGB (Red, Green and Blue) to detect color of vehicle image. The vehicle is separated from background by using optical flow. Blob analysis and feature-based are performed the type of vehicles. Feature-based is extracted by localized color clusters. This method can classify vehicle images into 3 types of car, pickup, and truck. The K-Nearest Neighbor algorithm is used to detect color possible. The proposed vehicle recognition method can be applied to spot target vehicles which match the suspect car input (type and color) and provide real-time and traffic surveillance information.","PeriodicalId":207985,"journal":{"name":"2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"The multi vehicle recognition using hybrid blob analysis and feature-based\",\"authors\":\"Anchisa Chantakamo, M. Ketcham\",\"doi\":\"10.1109/ICITEED.2015.7408989\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an approach method to detect vehicle color and to classify multi vehicle from video data. The multi vehicle is classified by blob analysis and feature-based. The proposed method uses a video file recorded by traffic surveillance camera as input. This technique applied RGB (Red, Green and Blue) to detect color of vehicle image. The vehicle is separated from background by using optical flow. Blob analysis and feature-based are performed the type of vehicles. Feature-based is extracted by localized color clusters. This method can classify vehicle images into 3 types of car, pickup, and truck. The K-Nearest Neighbor algorithm is used to detect color possible. The proposed vehicle recognition method can be applied to spot target vehicles which match the suspect car input (type and color) and provide real-time and traffic surveillance information.\",\"PeriodicalId\":207985,\"journal\":{\"name\":\"2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICITEED.2015.7408989\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITEED.2015.7408989","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The multi vehicle recognition using hybrid blob analysis and feature-based
This paper presents an approach method to detect vehicle color and to classify multi vehicle from video data. The multi vehicle is classified by blob analysis and feature-based. The proposed method uses a video file recorded by traffic surveillance camera as input. This technique applied RGB (Red, Green and Blue) to detect color of vehicle image. The vehicle is separated from background by using optical flow. Blob analysis and feature-based are performed the type of vehicles. Feature-based is extracted by localized color clusters. This method can classify vehicle images into 3 types of car, pickup, and truck. The K-Nearest Neighbor algorithm is used to detect color possible. The proposed vehicle recognition method can be applied to spot target vehicles which match the suspect car input (type and color) and provide real-time and traffic surveillance information.