{"title":"基于单通道连通元件标记和在位属性函数的改进车牌自动识别系统","authors":"Rohollah Mazrae Khoshki, S. Ganesan","doi":"10.1109/EIT.2015.7293378","DOIUrl":null,"url":null,"abstract":"This paper presents improved Automatic License Plate Recognition (ALPR) system based on Single Pass Connected Component Labeling (CCL). This research describes an ALPR system which is capable of distinguishing license plates under various conditions, such as distance from the camera, rotation angle between camera and vehicle (0° to +/-45°) and also poor illumination contrast condition (different weather condition, different lighting condition and physical tilted or damage of license plate). In our method, we apply adaptive thresholding filter to preprocessing step for image enhancement under various conditions, and then to find the location and characters of license plate at the same time we apply improved single pass Connected Component Labeling and regio property function that compared with other methods is fast and accurate. We determine the license plate characters and location according to appropriate size, aspect ratio, distance and connectivity of characters. Finally by using Optical Character Recognition (OCR) we find the characters on each license plate in an image. Image results show the accuracy and reliability of this method.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Improved Automatic License Plate Recognition (ALPR) system based on single pass Connected Component Labeling (CCL) and reign property function\",\"authors\":\"Rohollah Mazrae Khoshki, S. Ganesan\",\"doi\":\"10.1109/EIT.2015.7293378\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents improved Automatic License Plate Recognition (ALPR) system based on Single Pass Connected Component Labeling (CCL). This research describes an ALPR system which is capable of distinguishing license plates under various conditions, such as distance from the camera, rotation angle between camera and vehicle (0° to +/-45°) and also poor illumination contrast condition (different weather condition, different lighting condition and physical tilted or damage of license plate). In our method, we apply adaptive thresholding filter to preprocessing step for image enhancement under various conditions, and then to find the location and characters of license plate at the same time we apply improved single pass Connected Component Labeling and regio property function that compared with other methods is fast and accurate. We determine the license plate characters and location according to appropriate size, aspect ratio, distance and connectivity of characters. Finally by using Optical Character Recognition (OCR) we find the characters on each license plate in an image. Image results show the accuracy and reliability of this method.\",\"PeriodicalId\":415614,\"journal\":{\"name\":\"2015 IEEE International Conference on Electro/Information Technology (EIT)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Electro/Information Technology (EIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EIT.2015.7293378\",\"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 IEEE International Conference on Electro/Information Technology (EIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIT.2015.7293378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improved Automatic License Plate Recognition (ALPR) system based on single pass Connected Component Labeling (CCL) and reign property function
This paper presents improved Automatic License Plate Recognition (ALPR) system based on Single Pass Connected Component Labeling (CCL). This research describes an ALPR system which is capable of distinguishing license plates under various conditions, such as distance from the camera, rotation angle between camera and vehicle (0° to +/-45°) and also poor illumination contrast condition (different weather condition, different lighting condition and physical tilted or damage of license plate). In our method, we apply adaptive thresholding filter to preprocessing step for image enhancement under various conditions, and then to find the location and characters of license plate at the same time we apply improved single pass Connected Component Labeling and regio property function that compared with other methods is fast and accurate. We determine the license plate characters and location according to appropriate size, aspect ratio, distance and connectivity of characters. Finally by using Optical Character Recognition (OCR) we find the characters on each license plate in an image. Image results show the accuracy and reliability of this method.