Abstract: 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.

Key words: Gabor algorithm, anti sharpening mask filtering algorithm, feature extraction, extreme learning machine, occlusive facial recognition