基于改进Gabor算法的遮挡人脸智能识别方法

Intelligent Recognition Method for Occluded Faces Based on Improved Gabor Algorithm

为提高有遮挡人脸的识别精度,提出基于改进Gabor算法的遮挡人脸智能识别方法。首先,对人脸图像动态范围压缩,并选择反锐化掩模滤波算法展开图像增强处理;其次,利用Gabor滤波器对信息保留较完整、亮度较高的半边脸进行特征提取;最后将提取到的Gabor特征输入到极限学习机中完成遮挡人脸的智能识别。实验结果表明,所提方法对处理遮挡人脸图像具有良好的效果,且其对人脸图像识别具有精准度高、识别时间短等优点。

To improve the recognition accuracy of occluded faces,an intelligent recognition method for occluded faces based on the improved Gabor algorithm is proposed.Firstly,the dynamic range of facial images is compressed and the anti sharpening mask filtering algorithm is selected for image enhancement processing.Secondly,Gabor filters are used to extract features from half faces with relatively complete information preservation and high brightness.Finally,the extracted Gabor features are input into an extreme learning machine to achieve intelligent recognition of occluded faces.The experimental results show that the proposed method has good processing performance for occluded facial images,and the processed facial image recognition has high accuracy and short recognition time.