湖北民族学院学报（自然科学版）
湖北民族學院學報（自然科學版）
호북민족학원학보（자연과학판）
Journal of Hubei University for Nationalities（Natural Sciences Edition）
2015年
3期
300-303
,共4页
人脸识别%曲波变换%独立成分分析%特征提取%最近邻分类器
人臉識彆%麯波變換%獨立成分分析%特徵提取%最近鄰分類器
인검식별%곡파변환%독립성분분석%특정제취%최근린분류기
face recognition%curvelet transform%independent component analysis%feature extract%the nearest neighbor classifier
针对曲线特征更能反映人脸图像的主要特征和独立成分分析能够提取高阶信息的优势,提出了一种基于曲波变换与独立成分分析的人脸识别方法.首先将人脸图像进行曲波变换,选择粗尺度层系数作为曲波特征,然后对曲波特征下采样后进行独立成分分析,提取部分独立成分构成特征空间,最后根据最近邻分类器分类.在ORL和Yale人脸库上的相关实验表明:该方法在识别性能方面优于对比方法.
針對麯線特徵更能反映人臉圖像的主要特徵和獨立成分分析能夠提取高階信息的優勢,提齣瞭一種基于麯波變換與獨立成分分析的人臉識彆方法.首先將人臉圖像進行麯波變換,選擇粗呎度層繫數作為麯波特徵,然後對麯波特徵下採樣後進行獨立成分分析,提取部分獨立成分構成特徵空間,最後根據最近鄰分類器分類.在ORL和Yale人臉庫上的相關實驗錶明:該方法在識彆性能方麵優于對比方法.
침대곡선특정경능반영인검도상적주요특정화독립성분분석능구제취고계신식적우세,제출료일충기우곡파변환여독립성분분석적인검식별방법.수선장인검도상진행곡파변환,선택조척도층계수작위곡파특정,연후대곡파특정하채양후진행독립성분분석,제취부분독립성분구성특정공간,최후근거최근린분류기분류.재ORL화Yale인검고상적상관실험표명:해방법재식별성능방면우우대비방법.
As the main features of the faces can be better represented by the curvelet coefficients, and higher-order feature can be extracted by independent component analysis, a method of face recognition based on curvelet transform and ICA is proposed in this paper.Firstly, each of the images is decomposed using curvelet trasnform, and the low-frequency face image is selected as a sub-image;secondly,ICA is adopted to obtain independent components,and part of independent components are selected to constitute the feature space.Finally, the nearest neighbor classifier is used for identification.The experiment result on ORL and Yale face databases shows that the proposed method improved the recognition performance in comparison with comparative approach.
