| 基于光照自适应调节和模糊分类的人脸图像质量提升算法研究 |
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| 引用本文： | 景辉,戴琳琳,候亚伟,朱宇豪,随玉腾.基于光照自适应调节和模糊分类的人脸图像质量提升算法研究[J].铁路计算机应用,2023,32(2):1-6. |
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| 作者姓名： | 景辉 戴琳琳 候亚伟 朱宇豪 随玉腾 |
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| 作者单位： | 1.中国铁道科学研究院集团有限公司 电子计算技术研究所，北京 100081 |
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| 基金项目： | 中国国家铁路集团有限公司科技研究开发计划（P2020X001） |
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| 摘 要： | 针对铁路人脸识别闸机使用中影响人脸识别准确率的光照和模糊问题，文章提出一种人脸光照自适应调节算法，以提升非理想光照条件下的人脸识别准确率；设计了模糊识别模块，以挑选清晰的人脸图像，提升旅客移动场景的人脸识别准确率。在自建数据集中进行算法实验，实验结果表明，采用文章设计的算法，人脸识别准确率达到97.21%，能够满足实际应用的需求，具有推广价值。
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| 关 键 词： | 人脸识别 光照自适应调节 暗通道 图像去雾 Gamma矫正 |
| 收稿时间： | 2022-09-08 |
Face image quality improvement algorithm based on illumination adaptive adjustment and fuzzy classification |
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| Institution: | 1.Institute of Computing Technologies, China Academy of Railway Sciences Corporation Limited, Beijing, 100081, China2.Beijing Jingwei Information Technologies Co. Ltd., Beijing 100081, China |
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| Abstract: | Aiming at the illumination and blurring problems that affect the accuracy of face recognition in the use of railway face recognition gates, this paper proposed a face illumination adaptive adjustment algorithm to improve the accuracy of face recognition under non ideal lighting conditions, designed a clear fuzzy identification algorithm for face images to select clear face images and improve the accuracy of face recognition in passenger moving scenes. The algorithm experiments were carried out in self-built data sets. Experimental results show that the accuracy rate of face recognition reaches 97.21% using the algorithm designed in this paper, which can meet the needs of practical applications and has the value of popularization.. |
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