{"title":"基于神经网络和模板匹配的四轮车辆车牌号码提取","authors":"Anurag Kumar, Dipti Verma","doi":"10.1109/SMART50582.2020.9337084","DOIUrl":null,"url":null,"abstract":"One of the significant examination subjects of astute transportation framework and traffic observing framework is a License Plate Recognition (LPR) strategy. An LPR framework has a lot of logical utilization, for example, the installment of stopping expense, parkway cost charge, and traffic information assortment, traffic checking frameworks, etc. Nonetheless, LPR was set up to separate the data of vehicles by the picture of their tags. This paper presents a detail investigation of LCR framework and furthermore a proposed technique for applying the format coordinating methodology for character picture acknowledgment measure. The new methodology can be applied similarly to Indian cases. It depends on storing the picture of these number plates alongside a rundown of characters as passages in a table and afterward coordinating these sections individually with the vehicle plate. The new methodology is tried on different examples of separated tag pictures caught in outside condition. The outcome yield 80% acknowledgment precision, the strategy takes 0.306 seconds to play out the vehicle plate acknowledgment.","PeriodicalId":129946,"journal":{"name":"2020 9th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"29 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Extraction of Numbers from the Number Plates of 4 Wheel Vehicles using Neural Network and Template Matching\",\"authors\":\"Anurag Kumar, Dipti Verma\",\"doi\":\"10.1109/SMART50582.2020.9337084\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the significant examination subjects of astute transportation framework and traffic observing framework is a License Plate Recognition (LPR) strategy. An LPR framework has a lot of logical utilization, for example, the installment of stopping expense, parkway cost charge, and traffic information assortment, traffic checking frameworks, etc. Nonetheless, LPR was set up to separate the data of vehicles by the picture of their tags. This paper presents a detail investigation of LCR framework and furthermore a proposed technique for applying the format coordinating methodology for character picture acknowledgment measure. The new methodology can be applied similarly to Indian cases. It depends on storing the picture of these number plates alongside a rundown of characters as passages in a table and afterward coordinating these sections individually with the vehicle plate. The new methodology is tried on different examples of separated tag pictures caught in outside condition. The outcome yield 80% acknowledgment precision, the strategy takes 0.306 seconds to play out the vehicle plate acknowledgment.\",\"PeriodicalId\":129946,\"journal\":{\"name\":\"2020 9th International Conference System Modeling and Advancement in Research Trends (SMART)\",\"volume\":\"29 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 9th International Conference System Modeling and Advancement in Research Trends (SMART)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMART50582.2020.9337084\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 9th International Conference System Modeling and Advancement in Research Trends (SMART)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMART50582.2020.9337084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extraction of Numbers from the Number Plates of 4 Wheel Vehicles using Neural Network and Template Matching
One of the significant examination subjects of astute transportation framework and traffic observing framework is a License Plate Recognition (LPR) strategy. An LPR framework has a lot of logical utilization, for example, the installment of stopping expense, parkway cost charge, and traffic information assortment, traffic checking frameworks, etc. Nonetheless, LPR was set up to separate the data of vehicles by the picture of their tags. This paper presents a detail investigation of LCR framework and furthermore a proposed technique for applying the format coordinating methodology for character picture acknowledgment measure. The new methodology can be applied similarly to Indian cases. It depends on storing the picture of these number plates alongside a rundown of characters as passages in a table and afterward coordinating these sections individually with the vehicle plate. The new methodology is tried on different examples of separated tag pictures caught in outside condition. The outcome yield 80% acknowledgment precision, the strategy takes 0.306 seconds to play out the vehicle plate acknowledgment.