Patrick Matthew J. Chan, John Anthony C. Jose, R. Bedruz, E. Dadios
{"title":"基于遗传算法和特征提取的菲律宾车牌定位","authors":"Patrick Matthew J. Chan, John Anthony C. Jose, R. Bedruz, E. Dadios","doi":"10.1109/hnicem51456.2020.9400148","DOIUrl":null,"url":null,"abstract":"This study aims to focus on the license plate localization portion of an automated license plate recognition scheme. In order to achieve this, the study makes use of a genetic algorithm in order to perform a more systematic search over the input image; as well as Histogram of Oriented Gradients feature extraction technique in order to form the fitness function of the genetic algorithm. When the algorithm was tested, it was able to successfully localize the license plates within each of the multiple input images. In fact, even though the study was focused on 2014 series license plates, the program results also show that it was also able to roughly localize a license plate from another series as well.","PeriodicalId":230810,"journal":{"name":"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"306 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Philippine License Plate Localization Using Genetic Algorithm and Feature Extraction\",\"authors\":\"Patrick Matthew J. Chan, John Anthony C. Jose, R. Bedruz, E. Dadios\",\"doi\":\"10.1109/hnicem51456.2020.9400148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to focus on the license plate localization portion of an automated license plate recognition scheme. In order to achieve this, the study makes use of a genetic algorithm in order to perform a more systematic search over the input image; as well as Histogram of Oriented Gradients feature extraction technique in order to form the fitness function of the genetic algorithm. When the algorithm was tested, it was able to successfully localize the license plates within each of the multiple input images. In fact, even though the study was focused on 2014 series license plates, the program results also show that it was also able to roughly localize a license plate from another series as well.\",\"PeriodicalId\":230810,\"journal\":{\"name\":\"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)\",\"volume\":\"306 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/hnicem51456.2020.9400148\",\"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 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/hnicem51456.2020.9400148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Philippine License Plate Localization Using Genetic Algorithm and Feature Extraction
This study aims to focus on the license plate localization portion of an automated license plate recognition scheme. In order to achieve this, the study makes use of a genetic algorithm in order to perform a more systematic search over the input image; as well as Histogram of Oriented Gradients feature extraction technique in order to form the fitness function of the genetic algorithm. When the algorithm was tested, it was able to successfully localize the license plates within each of the multiple input images. In fact, even though the study was focused on 2014 series license plates, the program results also show that it was also able to roughly localize a license plate from another series as well.