摘要
人脸识别在实际应用中,通常由于光照的影响导致识别率的大幅下降。针对这一情况,该文从人脸图像预处理和特征提取算法两方面进行改进。文章首先采用了基于光照分量的算法进行人脸图像预处理,提高了算法对于光照的鲁棒性,然后提出了改进的结合了Gabor小波和LBP滤波的算法,并在有光照变化的标准人脸库上进行识别率测试。实验结果表明,该文算法对于变化光照的鲁棒性较高,在标准人脸库中的识别率最高可达到98.9%。
In practical application of the face recognition, the rate of recognition usually have a substantial decrease for the impact of different illuminations. In view of this situation, this paper improved from two aspects of the algorithm： image preprocessing and feature extraction. Firstly, we use the preprocessing algorithm based on the illumination to handle the face image, improved the robust of the illumination, and then put forward the improved combination of Gabor wavelet and LBP filter algorithm, meanwhile, we tested the recognition rate in the standard face database, which have different illuminations. The experimental results show that, this algorithm have a high robustness for the changes illuminations, the highest recognition rate in the standard face database can reach 98.9%.
作者
陈妍冰
张奇
刘琳婧
CHEN Yan-bing, ZHANG Qi , LIU Lin-jing （Xi＇an University of Science and Technology, Engineering Training Center, Xi＇an 710054,China）
出处
《电脑知识与技术》
2015年第2期147-149,共3页
Computer Knowledge and Technology
