{"title":"实时自动多风格车牌检测视频","authors":"Asmaa Elbamby, E. Hemayed, D. Helal, M. Rehan","doi":"10.1109/ICENCO.2016.7856460","DOIUrl":null,"url":null,"abstract":"Despite License Plate Recognition is mainly regarded as a solved problem; most of the techniques have been mainly developed for specific country or special formats which can strictly limits their applicability. There have been extensive studies of license plate detection since the 70s. The suggested approaches have difficulties in processing high-resolution imagery in real-time. This paper presents a novel algorithm for real-time automatic multi-style license plate detection in videos. The proposed algorithm can detect in a real time multiple license plates with various sizes in unfamiliar and complex environment. In this system, candidate plate regions are extracted using a preprocessing function to increase accuracy while decreasing computational time. Then a tree of LBP-based cascade classifiers is used to classify the candidate plate regions into one of the learned style. The proposed approach has been applied to Egyptian license plates with four different plate styles. The proposed approach achieved a success rate of 94% at 25 frames/sec using a moderate laptop.","PeriodicalId":332360,"journal":{"name":"2016 12th International Computer Engineering Conference (ICENCO)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Real-time automatic multi-style license plate detection in videos\",\"authors\":\"Asmaa Elbamby, E. Hemayed, D. Helal, M. Rehan\",\"doi\":\"10.1109/ICENCO.2016.7856460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite License Plate Recognition is mainly regarded as a solved problem; most of the techniques have been mainly developed for specific country or special formats which can strictly limits their applicability. There have been extensive studies of license plate detection since the 70s. The suggested approaches have difficulties in processing high-resolution imagery in real-time. This paper presents a novel algorithm for real-time automatic multi-style license plate detection in videos. The proposed algorithm can detect in a real time multiple license plates with various sizes in unfamiliar and complex environment. In this system, candidate plate regions are extracted using a preprocessing function to increase accuracy while decreasing computational time. Then a tree of LBP-based cascade classifiers is used to classify the candidate plate regions into one of the learned style. The proposed approach has been applied to Egyptian license plates with four different plate styles. The proposed approach achieved a success rate of 94% at 25 frames/sec using a moderate laptop.\",\"PeriodicalId\":332360,\"journal\":{\"name\":\"2016 12th International Computer Engineering Conference (ICENCO)\",\"volume\":\"100 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 12th International Computer Engineering Conference (ICENCO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICENCO.2016.7856460\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 12th International Computer Engineering Conference (ICENCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICENCO.2016.7856460","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time automatic multi-style license plate detection in videos
Despite License Plate Recognition is mainly regarded as a solved problem; most of the techniques have been mainly developed for specific country or special formats which can strictly limits their applicability. There have been extensive studies of license plate detection since the 70s. The suggested approaches have difficulties in processing high-resolution imagery in real-time. This paper presents a novel algorithm for real-time automatic multi-style license plate detection in videos. The proposed algorithm can detect in a real time multiple license plates with various sizes in unfamiliar and complex environment. In this system, candidate plate regions are extracted using a preprocessing function to increase accuracy while decreasing computational time. Then a tree of LBP-based cascade classifiers is used to classify the candidate plate regions into one of the learned style. The proposed approach has been applied to Egyptian license plates with four different plate styles. The proposed approach achieved a success rate of 94% at 25 frames/sec using a moderate laptop.