Low resolution face recognition algorithm based on MB-LBP Online publication date: Tue, 17-Oct-2023
by Bin Fang
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 27, No. 4, 2023
Abstract: 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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Mining and Bioinformatics (IJDMB):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com