东南大学学报（英文版）2020，Vol.36Issue(4)：407-413,7.DOI:10.3969/j.issn.1003-7985.2020.04.006
基于中心对称四重模式的光照不变度量
Centre symmetric quadruple pattern-based illumination invariant measure
摘要
Abstract
A centre symmetric quadruple pattern-based illumination invariant measure(CSQPIM)is proposed to tackle severe illumination variation face recognition.First,the subtraction of the pixel pairs of the centre symmetric quadruple pattern(CSQP)is defined as the CSQPIM unit in the logarithm face local region,which may be positive or negative.The CSQPIM model is obtained by combining the positive and negative CSQPIM units.Then,the CSQPIM model can be used to generate several CSQPIM images by controlling the proportions of positive and negative CSQPIM units.The single CSQPIM image with the saturation function can be used to develop the CSQPIM-face.Multi CSQPIM images employ the extended sparse representation classification(ESRC)as the classifier,which can create the CSQPIM image-based classification(CSQPIMC).Furthermore,the CSQPIM model is integrated with the pre-trained deep learning(PDL)model to construct the CSQPIM-PDL model.Finally,the experimental results on the Extended Yale B,CMU PIE and Driver face databases indicate that the proposed methods are efficient for tackling severe illumination variations.关键词
中心对称四重模式/光照不变度量/剧烈光照变化/单样本人脸识别Key words
centre symmetric quadruple pattern/illumination invariant measure/severe illumination variations/single sample face recognition分类
信息技术与安全科学引用本文复制引用
胡长晖,张扬,路小波,刘攀..基于中心对称四重模式的光照不变度量[J].东南大学学报（英文版）,2020,36(4):407-413,7.基金项目
Foundation items:The National Natural Science Foundation of China(No.61802203),the Natural Science Foundation of Jiangsu Province(No.BK20180761),China Postdoctoral Science Foundation(No.2019M651653),Postdoctoral Research Funding Program of Jiangsu Province(No.2019K124). （No.61802203）
