Face Recognition Algorithm Based on Broad Learning System

Face recognition is a well-known issue in the realm of image processing, which has made tremendous strides in recent years, owing to the rapid development of artificial intelligence technology, and has become one of the most prominent research areas in a variety of fields. However, when uncontrollable variables such as light, face occlusion, and expression change are present, the recognition accuracy suffers as a result of the change in facial features. Face recognition in a complex environment is challenging since the accuracy of the algorithm is insufficient. This paper proposes a k-means clustering face recognition method based on the Broad Learning System (BLS),and discusses the principle and performance of the algorithm. The experimental results demonstrate that the proposed strategy improves identification accuracy and is more resistant to noise interference without requiring any changes to the model structure.