Low resolution face recognition algorithm based on MB-LBP

Due to the low accuracy, poor stability, and long time consumption of current face recognition methods, a low resolution face recognition algorithm based on MB-LBP is proposed. Firstly, the facial edge image is processed through binarisation, followed by scale normalisation to accurately locate the face and the final cropped facial image. Then, segmented linear transformation is used for image enhancement processing. Finally, MB-LBP is used to extract features, and the Euclidean distance and cosine angle between the extracted feature vectors and the feature vectors extracted from the face database are calculated to achieve dual matching of facial images and achieve face recognition. The results show that the quality of the results obtained by this algorithm is good, with peak signal-to-noise ratio and recognition accuracy of 160 dB and 100%, variance of 0.01, and recognition time of 1.8 s, indicating that the algorithm proposed in this paper has reliable application performance.