【摘要】 人脸识别领域中,Gabor特征人脸表示方法因其在应用中获得的高首选识别率而被认为是一种理想的人脸特征表示方法。文章用一种全新的量化评价方法,结合配准精度和识别率,从误配准鲁棒性角度评价Gabor特征在人脸识别中的优越性。实验表明,和图像灰度信息特征相比,Gabor特征不仅在精确配准时具有高识别率,而且对由于人脸特征定位不精确而导致的图像变化的鲁棒性也更强。更多还原

【Abstract】 Gabor feature has been widely recognized as a desirous representation for face recognition in terms of its high recognition rate.This paper evaluates Gabor feature for face recognition from a new angle of its robustness to mis-alignment using a novel quantificational evaluation method which combines the alignment precision with the recognition accuracy.This experiments show that,compared with the gray-level intensity,Gabor feature is much more robust to image variation caused by the imprecision of facial feature localization,which further support the feasibility of Gabor representation.更多还原