M. Nazarkevych, Yaroslav Voznyi, V. Hrytsyk, Ivanna Klyujnyk, Bohdana Havrysh, N. Lotoshynska
{"title":"基于机器学习的生物特征图像识别","authors":"M. Nazarkevych, Yaroslav Voznyi, V. Hrytsyk, Ivanna Klyujnyk, Bohdana Havrysh, N. Lotoshynska","doi":"10.1109/ELIT53502.2021.9501064","DOIUrl":null,"url":null,"abstract":"The method of biometric prints classification by means of machine learning is offered. The “k-means” method was used to identify biometric images. Labeled sample data for learning and testing processes are generated. Experimental results point to the benefit of the presented method of integration of global and structured data and indicate that “k-means” is a promising approach to fingerprint classification. The development of biometrics leads to the creation of security systems with better degrees of recognition and with fewer errors than security systems on traditional media. Machine learning was performed using a number of samples from a known biometric database, and verification / testing was performed with samples from the same database that were not included in the training data set.","PeriodicalId":164798,"journal":{"name":"2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Identification of Biometric Images by Machine Learning\",\"authors\":\"M. Nazarkevych, Yaroslav Voznyi, V. Hrytsyk, Ivanna Klyujnyk, Bohdana Havrysh, N. Lotoshynska\",\"doi\":\"10.1109/ELIT53502.2021.9501064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The method of biometric prints classification by means of machine learning is offered. The “k-means” method was used to identify biometric images. Labeled sample data for learning and testing processes are generated. Experimental results point to the benefit of the presented method of integration of global and structured data and indicate that “k-means” is a promising approach to fingerprint classification. The development of biometrics leads to the creation of security systems with better degrees of recognition and with fewer errors than security systems on traditional media. Machine learning was performed using a number of samples from a known biometric database, and verification / testing was performed with samples from the same database that were not included in the training data set.\",\"PeriodicalId\":164798,\"journal\":{\"name\":\"2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ELIT53502.2021.9501064\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELIT53502.2021.9501064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification of Biometric Images by Machine Learning
The method of biometric prints classification by means of machine learning is offered. The “k-means” method was used to identify biometric images. Labeled sample data for learning and testing processes are generated. Experimental results point to the benefit of the presented method of integration of global and structured data and indicate that “k-means” is a promising approach to fingerprint classification. The development of biometrics leads to the creation of security systems with better degrees of recognition and with fewer errors than security systems on traditional media. Machine learning was performed using a number of samples from a known biometric database, and verification / testing was performed with samples from the same database that were not included in the training data set.