Meivel S, Indira Devi K, Uma Maheswari S, Vijaya Menaka J
Department of ECE, Kumarasamy College of Engineering, India.
Department of ICE, GRG Polytechnic College, India.
Mater Today Proc. 2021 Feb 20. doi: 10.1016/j.matpr.2020.12.1042.
This paper describes mask detection using Matlab when complex images in the dataset. Matlab specified the Faster R-CNN algorithm and Dataset allotment for mask detection. This paper manages complex pictures using facial recognition packages. The Faster R-CNN methodology used in the security system and the medical system. The proposed work balanced face restriction, color changes, brightness changes, and contrast changes. Segmentation and feature extraction used in face restriction of the person image. We chose RCNN, Fast RCNN, and Faster RCNN algorithm for detecting Mask detection and Social distance. Regions with Convolutional neural network Based on Mixing pictures, pixel prediction, and specific enhancements. The main objective was to solving multiple and multitask picture detection problems with speed rates. The Methodology used for face detection and detection of Unmask person in a dataset of face database.
本文描述了在数据集中存在复杂图像时使用Matlab进行口罩检测的方法。Matlab指定了用于口罩检测的Faster R-CNN算法和数据集分配。本文使用面部识别软件包来处理复杂图片。Faster R-CNN方法应用于安全系统和医疗系统。所提出的工作平衡了面部约束、颜色变化、亮度变化和对比度变化。在人物图像的面部约束中使用了分割和特征提取。我们选择了RCNN、Fast RCNN和Faster RCNN算法来检测口罩佩戴情况和社交距离。基于混合图片、像素预测和特定增强的卷积神经网络区域。主要目标是以速度率解决多任务和多图片检测问题。该方法用于在人脸数据库的数据集中进行人脸检测和未戴口罩人员的检测。
