{"title":"基于辐射能量和小波域子块DCT的红外人脸识别","authors":"Xiao-Wei Liu, Zhihua Xie, Cui-Qun He, Guodon Liu","doi":"10.1109/ICWAPR.2010.5576437","DOIUrl":null,"url":null,"abstract":"A novel infrared face recognition method is proposed in this paper. In this method, according to Stefan-Boltzmann's law, the raw thermal images are transformed to the radiative energy images, and they are decomposed using two scales' discrete wavelet transform. The components of low frequency sub-bands are partitioned into sub-blocks, then, they are transformed by DCT. Each face is represented by the coefficients extracted from the sub-blocks in DCT domain. Finally, according to the discriminative power, different sub-blocks in DCT domain can be assigned different weights. Experiments demonstrate the method proposed perform very well on recognition rates as compared to other methods.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Infrared face recognition based on radiative energy and sub-block DCT in wavelet domain\",\"authors\":\"Xiao-Wei Liu, Zhihua Xie, Cui-Qun He, Guodon Liu\",\"doi\":\"10.1109/ICWAPR.2010.5576437\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel infrared face recognition method is proposed in this paper. In this method, according to Stefan-Boltzmann's law, the raw thermal images are transformed to the radiative energy images, and they are decomposed using two scales' discrete wavelet transform. The components of low frequency sub-bands are partitioned into sub-blocks, then, they are transformed by DCT. Each face is represented by the coefficients extracted from the sub-blocks in DCT domain. Finally, according to the discriminative power, different sub-blocks in DCT domain can be assigned different weights. Experiments demonstrate the method proposed perform very well on recognition rates as compared to other methods.\",\"PeriodicalId\":219884,\"journal\":{\"name\":\"2010 International Conference on Wavelet Analysis and Pattern Recognition\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Wavelet Analysis and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICWAPR.2010.5576437\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Wavelet Analysis and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWAPR.2010.5576437","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Infrared face recognition based on radiative energy and sub-block DCT in wavelet domain
A novel infrared face recognition method is proposed in this paper. In this method, according to Stefan-Boltzmann's law, the raw thermal images are transformed to the radiative energy images, and they are decomposed using two scales' discrete wavelet transform. The components of low frequency sub-bands are partitioned into sub-blocks, then, they are transformed by DCT. Each face is represented by the coefficients extracted from the sub-blocks in DCT domain. Finally, according to the discriminative power, different sub-blocks in DCT domain can be assigned different weights. Experiments demonstrate the method proposed perform very well on recognition rates as compared to other methods.