基于格拉斯曼流型的模糊人脸图像识别方法  

The Approach of Fuzzy Face Recognition Based on the Grassmannian Manifold

作　　者：叶娟[1] 陈启买[2] 陈君梅[1] 

机构地区：[1]广东科学技术职业学院,广东广州510640 [2]华南师范大学,广东广州510631

出　　处：《信息与控制》2015年第4期507-512,共6页Information and Control

基　　金：广东省高等学校优秀青年教师培养计划资助项目(Yq2013177);广东省自然科学基金资助项目(S2013010011519)

摘　　要：针对模糊人脸图像识别中图像识别精度低的问题,提出一种基于改进的格拉斯曼流型的模糊人脸图像识别算法.在零噪声和已知模糊基的最大尺寸的条件下,建构由图像与预设定最大尺寸的完备正交基卷积得到的子空间,并证明了清晰图像和模糊图像得到的子空间是相同的.将构建的子空间当作格拉斯曼流型中的一个点,采用这种子空间表示方法来进行模糊图像的识别,同时研究了在模糊量具有同质性和空变性条件下的模糊图像识别问题.仿真实验结果表明,本文提出的方法能够有效提高人脸识别的精确度且具有较高的识别率.To address the problem of low image recognition accuracy in facial recognition software, a fuzzy face im- age recognition algorithm based on the improved Grassmannian manifold is proposed. Under the conditions of zero noise and the maximum size of the fuzzy basis being known, the subspace （ obtained from images and complete orthogonal basis convolution, where the maximum size has been preset） is constructed, and the sub- spaces obtained from clear images and fuzzy images are demonstrated to be the same. Flurry image recognition by adopting this subspace presentation is tested by taking the constructed subspace as a point in the Grass- mannian manifold. Moreover, the flurry image recognition problem under the condition that the fuzzy quantity exhibits both homogeneity and mutability is studied. The simulation results show that the method proposed in this paper will improve facial recognition accuracy and achieve a high recognition rate.

关 键 词：模糊基 子空间 人脸识别 格拉斯曼流型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]