Gabor滤波器和支持向量机相融合的人脸识别

Face Recognition Based on Gabor Filter and Support Vector Machine

人脸识别是一种具有实际应用前景的技术,针对人脸识别过程中特征提取和分类器构建等问题,提出一种基于Gabor滤波器和支持向量机相融合的人脸识别方法。首先收集人脸样本组成图像训练库,并提取人脸图像的Gabor特征,生成人脸识别数据,然后通过支持向量机对人脸图像库进行训练,建立人脸图像的分类器,最后采用ORL人脸库进行测试实验。实验结果表明,与其他人脸识别方法相比,本文方法可以实现更加精准的人脸分类与识别,对人脸识别更具有适用性。

Face recognition is an important technology with practical application prospect, according to the feature extraction and classifier construction in the process of face recognition, a face recognition method based on Gabor filter and support vector machine is proposed in this paper. Firstly, the face image database is collected and the Gabor fea- tures are extracted, and secondly support vector machine is used to train face image sample and the face image classifier is established, and lastly the face database ORL is used to test the classifier performance. Experimental results show that the proposed face recognition method can achieve higher accuracy of face recognition compared with other face recogni- tion methods, and it is more suitable for face recognition.