[1]余拓,陈莹.基于加权边缘弱化引导滤波的人脸光照补偿[J].智能系统学报,2018,13(3):373-379.[doi:10.11992/tis.201612011]
YU Tuo,CHEN Ying.Face illumination compensation based on weighted edge-weakening guided image filter[J].CAAI Transactions on Intelligent Systems,2018,13(3):373-379.[doi:10.11992/tis.201612011]
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YU Tuo,CHEN Ying.Face illumination compensation based on weighted edge-weakening guided image filter[J].CAAI Transactions on Intelligent Systems,2018,13(3):373-379.[doi:10.11992/tis.201612011]
基于加权边缘弱化引导滤波的人脸光照补偿
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
13
期数:
2018年第3期
页码:
373-379
栏目:
学术论文—机器感知与模式识别
出版日期:
2018-05-05
- Title:
- Face illumination compensation based on weighted edge-weakening guided image filter
- Keywords:
- face recognition; illumination compensation; illumination model; gaussian blur; guided image filter; ridge regression; loss function; self-quotient image
- 分类号:
- TP391
- 摘要:
- 光照的变化是影响人脸识别结果的重要因素之一，针对这一问题，提出一种基于加权边缘弱化引导滤波的人脸光照补偿方法。首先为引导滤波损失函数添加一个可区分边缘细节的惩罚项，然后为惩罚项加权，加权系数由正面光照样本的类间平均脸计算得到，最后将滤波后的图像作为自商图中的平滑图，得到光照补偿图像。实验结果表明，该方法弱化了人脸平滑区域由光照造成的边缘细节噪声，且使用光照补偿图像作为人脸识别输入，能有效提高人脸识别准确率，特别在光照大范围变化时，识别准确率提升程度更高。
- Abstract:
- The variation of illumination is an important factor affecting the face recognition effect. Focusing on this problem, this study proposes a face illumination compensation based on a weighted edge-weakening guided image filter. First, a penalty item, whose edge details can be distinguished, was added into the loss function of the guided image filter. The penalty item was then weighted by a coefficient that was calculated by an inner-class mean face image of positive illumination samples. Finally, the filtered image was used as the smooth image in the self-quotient image to obtain the illumination compensation image. The experimental results showed that the proposed method can weaken the edge noise caused by the illumination in the smooth face area. Moreover, the face recognition rate can be improved using the illumination compensation image as the face recognition input, especially in the case of a large illumination variation.
- 参考文献/References:
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备注/Memo
收稿日期:2016-12-09。
基金项目:国家自然科学基金项目（61573168）.
作者简介:余拓,男,1993年生,硕士研究生,主要研究方向为人脸识别;陈莹,女,1976年生,教授,博士,CCF会员,主要研究方向为计算机视觉、模式识别。
通讯作者:陈莹.E-mail:chenying@jiangnan.edu.cn.
更新日期/Last Update:
2018-06-25