改进的MSF-VQ人脸特征提取方法

摘要

MSF-VQ是一种用于人脸识别的图像特征. 它先使用预先确定的码书计算出图片的向量量化直方图特征,再通过马尔科夫稳态特征对直方图进行扩展, 从而得到MSF-VQ特征. MSF-VQ特征在人脸识别中表现出较高的识别准确率. 但是它在码书的确定和空间信息表达上仍有一些不足之处. 针对这两个方面, 本文提出了一种改进的方法. 首先根据人脸数据集来计算码书, 从而提高向量量化直方图对人脸的分辨能力, 然后通过结合多个方向上采样的MSF特征, 增加MSF-VQ特征包含的空间位置信息. 实验结果表明, 改进的MSF-VQ方法具有更高的人脸识别准确率.%MSF-VQ is a kind of image features for face recognition. Firstly, vector quantization histogram feature is calculated with the predetermined codebook. Then, the histogram is extended through Markov stationary feature to get MSF-VQ features. MSF-VQ features for face recognition show high recognition rate. But it can still be improved on the determination of codebook and spatial information expression. According to these two points, this study puts forward an improved method. It first calculates the codebook based on the facial data set, so as to improve face resolution capability of vector quantization histogram, and then combines several MSF features calculated from different directions sampling, to increase spatial location information contained by MSF-VQ feature. Experimental results show that the improved MSF-VQ method has higher face recognition rate.