{"title":"Weighted Edit Distance for Country Code Recognition in License Plates","authors":"K. Chumachenko, Alexandros Iosifidis, M. Gabbouj","doi":"10.23919/eusipco55093.2022.9909869","DOIUrl":null,"url":null,"abstract":"This paper presents the problem of country code recognition from li-cense plate images. We propose an approach based on character de-tection and subsequent clustering for country code localization. We further propose three weighted Edit Distance metrics for country of origin prediction from imperfect detections, namely based on char-acter similarity, detection confidence, and relative operation impor-tance. Experimental results show the benefit of proposed approaches on real-world data. The proposed method is lightweight and inde-pendent of the underlying object detector, facilitating its application on edge devices.","PeriodicalId":231263,"journal":{"name":"2022 30th European Signal Processing Conference (EUSIPCO)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 30th European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/eusipco55093.2022.9909869","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents the problem of country code recognition from li-cense plate images. We propose an approach based on character de-tection and subsequent clustering for country code localization. We further propose three weighted Edit Distance metrics for country of origin prediction from imperfect detections, namely based on char-acter similarity, detection confidence, and relative operation impor-tance. Experimental results show the benefit of proposed approaches on real-world data. The proposed method is lightweight and inde-pendent of the underlying object detector, facilitating its application on edge devices.