Improving Accuracy in Face Mask Detection Based on Opencv Compared with Viola-Jones Method for Pandemic Control
Keywords:
OpenCV, Novel Facemask Detection, Accuracy, Deep Learning, Machine Learning, COVID19.Abstract
Aim:This work aims to improve the accuracy in Face Mask detection based on OpenCV compared with the Viola-Jones method for Pandemic Control. Materials and Methods: OpenCV with ViolaJones methods are chosen as two groups and each group with 15 samples respectively, which are collected using the training image datasets.G Power = 0.8. Result: The independent sample t-test result shows that the accuracy in (%) is improved for the OpenCV based face mask detection method with a mean (96.52) when compared with the Viola-Jones method (81.24) with a significance (p<0.05). Conclusion: The analysis shows that the accuracy of OpenCV based facemask detection is significantly better compared to the Viola-Jones method.