针对人脸图像易受光线和表情影响的特点,提出了一种基于二进小波变换和仿生模式识别的人脸识别方法。应用样条二进小波对人脸图像进行处理,对得到的细节子图进行融合。在FFT和PCA处理与降维后,用仿生模式识别进行学习和识别。实验结果表明,该方法比传统方法具有更高的识别率。
Aiming at robustness of face recognition under the condition of illumination perturbations and facial variety, a face recognition method based on dyadic wavelet transform and biomimetic pattern recognition is proposed in this paper. The spline dyadic wavelet is applied to face images. The detail subbands are merged by concatenation. The facial images are treated and reduced dimension respectively by FFT (Fast Fourier Transform) and PCA (Principal Component Analysis). The feature vectors are learned and recognized by biomimetic pattern recognition. The experimental results prove that the correct recognition rate of the method in this paper is higher than traditional recognition method.