计算机工程与应用2015，Vol.51Issue(24)：176-179,4.DOI:10.3778/j.issn.1002-8331.1312-0159
融合全局和局部特征的人脸识别算法
Face recognition based on global and local information
摘要
Abstract
The existing face recognition algorithms lack the ability of automatic regulation for illumination variation. This paper describes a face recognition algorithm based on both global and local feature. Principal Component Analysis is performed to extract global features. A special strategy is used to combine different local features according to their image entropy. Bayes integration is adopted to fuse both global and local features and the final result is given. The experiments demonstrate that this algorithm can combine global and local information well and improve the efficiency of the face recognition rate.关键词
人脸识别/局部特征/全局特征/主成分分析/图像熵/贝叶斯原理Key words
face recognition/local feature/global feature/Principal Component Analysis(PCA)/image entropy/Bayes theory分类
信息技术与安全科学引用本文复制引用
杨军,张瑞峰,林岩龙,王小鹏..融合全局和局部特征的人脸识别算法[J].计算机工程与应用,2015,51(24):176-179,4.基金项目
国家自然科学基金(No.61261029) （No.61261029）
中国博士后科学基金项目(No.2013M542396) （No.2013M542396）
人社部留学人员科技活动项目择优资助 （）
甘肃省自然科学基金(No.1208RJZA243) （No.1208RJZA243）
陇原青年创新人才扶持计划(No.201182). （No.201182）
