摘要
提出了一种基于图像分块的FDA(Fisher linear discriminating analysis)人脸识别方法,该方法首先对原始图像进行分块,再对分块得到的子图像利用FDA进行鉴别分析。其特点是能有效地抽取图像的局部特征,对人脸表情和光照条件变化较大的图像表现尤为突出。在ORL人脸库上用单训练样本取得了90.83%的识别结果。
In this paper, a method of FDA for face recognition is presented basing on image segmentation. First, the original images are divided into modular images, which are also called sub- images; then, the well - known FDA method is directly used to the sub - images obtained from the previous step. The advantage of the represented way is that the local discriminant features of the original patterns can be efficiently extracted, and it is really true of the images that have large variations in facial expression and lighting. The ORL face image database is made use of to simulate, and when the training sample is only one, the recognition rate of 90.83 percent is achieved.
出处
《河北工程大学学报（自然科学版）》
CAS
2008年第3期84-87,共4页
Journal of Hebei University of Engineering:Natural Science Edition
关键词
人脸识别
区域分块
线性鉴别分析
face recognition
image segmentation
linear discriminant analysis
