Research Article
Research on Preprocessing Algorithm of Two-Camera Face Recognition Attendance Image Based on Artificial Intelligence
@INPROCEEDINGS{10.1007/978-3-030-51103-6_16, author={Lin-lin Tian and Wan-li Teng and Hai-hong Bian}, title={Research on Preprocessing Algorithm of Two-Camera Face Recognition Attendance Image Based on Artificial Intelligence}, proceedings={Multimedia Technology and Enhanced Learning. Second EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part II}, proceedings_a={ICMTEL PART 2}, year={2020}, month={7}, keywords={Two camera face recognition Image preprocessing Artificial intelligence technology Noise reduction processing}, doi={10.1007/978-3-030-51103-6_16} }- Lin-lin Tian
Wan-li Teng
Hai-hong Bian
Year: 2020
Research on Preprocessing Algorithm of Two-Camera Face Recognition Attendance Image Based on Artificial Intelligence
ICMTEL PART 2
Springer
DOI: 10.1007/978-3-030-51103-6_16
Abstract
The traditional double-camera face recognition attendance image preprocessing algorithm can not distinguish the target from the complex background. In order to solve this problem, an artificial intelligence based double-camera face recognition attendance image preprocessing algorithm is proposed. First, artificial intelligence technology is used to extract the features of face recognition attendance image, and then spatial denoising algorithm is used to remove the noise of face recognition attendance image. On this basis, multi-channel texture weighting algorithm is used to realize the double-camera face recognition attendance image preprocessing. Therefore, a double-camera face recognition image preprocessing algorithm based on artificial intelligence is completed. In the experiment, the infrared image of the face is tested to see whether the evaluation factors obtained by the two algorithms can distinguish the target from the complex background. Experimental results show that the algorithm has a short computing time and can distinguish targets in complex background in a short time.
