{"title":"基于FFBN分类器的车牌字符识别系统的设计与实现","authors":"P. Reji, V. Dharun","doi":"10.15866/irecos.v12i1.10928","DOIUrl":null,"url":null,"abstract":"In this paper, a coercive and dynamic Automatic Vehicle Number Plate Recognition (AVNPR) scheme is obtained, a throng supervision structure able to detect Indian license plates; it is a cardinal procedure in Intelligent Transportation Systems (ITS). The progression of detection and identification of License Plates in this proposed system is divided in four sections: Image Pre-processing, License Plate Localization, Character Segmentation and Character Recognition. A Feed Forward Back-propagation Neural network (FFBN) Classifier is engaged for this particular system for License Plate exposure and features mining of License Plate characters. The outcomes demonstrate that the proposed system can successfully distinguish and identify License Plates even in problematical surroundings. A superior entitlement of accurateness has been received for the implication of this method and it is confirmed to be 92.13% for the withdrawal of License Plate area and 90.55% identifications of License Plate characters with greater concert than conventional approaches. The planned structure has been put into practice in MATLAB.","PeriodicalId":392163,"journal":{"name":"International Review on Computers and Software","volume":"95 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design and Implementation of a Vehicle License Plate Characters Recognition System based on FFBN Classifier\",\"authors\":\"P. Reji, V. Dharun\",\"doi\":\"10.15866/irecos.v12i1.10928\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a coercive and dynamic Automatic Vehicle Number Plate Recognition (AVNPR) scheme is obtained, a throng supervision structure able to detect Indian license plates; it is a cardinal procedure in Intelligent Transportation Systems (ITS). The progression of detection and identification of License Plates in this proposed system is divided in four sections: Image Pre-processing, License Plate Localization, Character Segmentation and Character Recognition. A Feed Forward Back-propagation Neural network (FFBN) Classifier is engaged for this particular system for License Plate exposure and features mining of License Plate characters. The outcomes demonstrate that the proposed system can successfully distinguish and identify License Plates even in problematical surroundings. A superior entitlement of accurateness has been received for the implication of this method and it is confirmed to be 92.13% for the withdrawal of License Plate area and 90.55% identifications of License Plate characters with greater concert than conventional approaches. The planned structure has been put into practice in MATLAB.\",\"PeriodicalId\":392163,\"journal\":{\"name\":\"International Review on Computers and Software\",\"volume\":\"95 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Review on Computers and Software\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15866/irecos.v12i1.10928\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review on Computers and Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15866/irecos.v12i1.10928","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design and Implementation of a Vehicle License Plate Characters Recognition System based on FFBN Classifier
In this paper, a coercive and dynamic Automatic Vehicle Number Plate Recognition (AVNPR) scheme is obtained, a throng supervision structure able to detect Indian license plates; it is a cardinal procedure in Intelligent Transportation Systems (ITS). The progression of detection and identification of License Plates in this proposed system is divided in four sections: Image Pre-processing, License Plate Localization, Character Segmentation and Character Recognition. A Feed Forward Back-propagation Neural network (FFBN) Classifier is engaged for this particular system for License Plate exposure and features mining of License Plate characters. The outcomes demonstrate that the proposed system can successfully distinguish and identify License Plates even in problematical surroundings. A superior entitlement of accurateness has been received for the implication of this method and it is confirmed to be 92.13% for the withdrawal of License Plate area and 90.55% identifications of License Plate characters with greater concert than conventional approaches. The planned structure has been put into practice in MATLAB.