{"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}
引用次数: 0
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.