{"title":"红外图像分析用于人脸识别","authors":"Muhammad Eka Setio Aji, R. Alfanz, E. Prakasa","doi":"10.1109/icci54321.2022.9756103","DOIUrl":null,"url":null,"abstract":"Thermal infrared images have potential to captured the images without being affected by illumination. In this paper, we proposed a face recognition method using infrared images. The Convolution Neural Network are used to extract feature from the images with the combination of Haar Cascade, and Local Binary Pattern to indicate the face area. At the same time, images were acquired by using infrared camera and webcam. Compared between infrared and visible images, the experimental result from infrared images by using Convolutional Neural Network in combined with Haar Cascade show superiority in the measurement result of several parameters used with the highest score in accuracy up to 98% which outperforms the other experiment in this paper.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Infrared Image Analysis for Human Face Recognition\",\"authors\":\"Muhammad Eka Setio Aji, R. Alfanz, E. Prakasa\",\"doi\":\"10.1109/icci54321.2022.9756103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Thermal infrared images have potential to captured the images without being affected by illumination. In this paper, we proposed a face recognition method using infrared images. The Convolution Neural Network are used to extract feature from the images with the combination of Haar Cascade, and Local Binary Pattern to indicate the face area. At the same time, images were acquired by using infrared camera and webcam. Compared between infrared and visible images, the experimental result from infrared images by using Convolutional Neural Network in combined with Haar Cascade show superiority in the measurement result of several parameters used with the highest score in accuracy up to 98% which outperforms the other experiment in this paper.\",\"PeriodicalId\":122550,\"journal\":{\"name\":\"2022 5th International Conference on Computing and Informatics (ICCI)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 5th International Conference on Computing and Informatics (ICCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icci54321.2022.9756103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th International Conference on Computing and Informatics (ICCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icci54321.2022.9756103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Infrared Image Analysis for Human Face Recognition
Thermal infrared images have potential to captured the images without being affected by illumination. In this paper, we proposed a face recognition method using infrared images. The Convolution Neural Network are used to extract feature from the images with the combination of Haar Cascade, and Local Binary Pattern to indicate the face area. At the same time, images were acquired by using infrared camera and webcam. Compared between infrared and visible images, the experimental result from infrared images by using Convolutional Neural Network in combined with Haar Cascade show superiority in the measurement result of several parameters used with the highest score in accuracy up to 98% which outperforms the other experiment in this paper.