基于局部三值微分模式的人脸识别方法

Face recognition method base local ternary derivative pattern

为了减轻噪声干扰,提取更为丰富的人脸鉴别特征,提出了局部三值微分模式算子。通过判断近邻像素灰度值是否在某个范围内对当前像素的局部微分模式从二值扩展到三值,然后将扩展后编码的Uniform模式的空间直方图依次相连形成人脸的特征向量,采用卡方统计算样本相似度并进行分类。在ORL、Yale和CAS-PEAL-R1人脸数据库上的实验结果表明,提出的算法的识别性能优于局部二值模式和局部微分模式。、

In order to reduce noise and extract richer discriminant feature, the local ternary local derivative pattern operator was proposed. By determining whether the adjacent pixel gray values within a certain range, the local derivative pattern of current pixel was extended from binary to ternary, and the face feature vector was formed by sequentially connecting the uniform pattern of the space histogram of the encode. The chi-square statistic was used to calculate the sample similarity of face feature vector. The experimental results on ORL, Yale and CAS -PEAL -R1 face database show that the recognition performance of the proposed algorithm was superior to local binary pattern and local derivative pattern.