关键词: 相对梯度, 人脸识别, 二维主成分分析, 二维Fisher线性判别分析

Abstract: Based on the original relative gradient operator, the authors proposed a new relative gradient operator and combined it with 2DPCA or 2DFLD. A face recognition algorithm based on this new relative gradient operator was also put forward. Experimental results on AR and Yale_B face database show that, the method has robustness to the complex change like various expression and lighting condition. The recognition accuracy of the method is much higher than 2DPCA, 2DFLD and face recognition based on the original relative gradient operator. What is more, experiments were done on three different sizes of windows, which confirms that, when the window size is 3×3, the recognition result is relatively the best.

Key words: relative gradient, face recognition, 2-Dimensional Principal Component Analysis (2DPCA), 2-Dimensional Fisher Linear Discriminant Analysis (2DFLD)