Research And Development Of Smart Community Security System Based On Face Detection

With the development of the field of deep learning,face detection algorithms have been widely used in many fields.Coupled with the sustained economic development of our country and the significant improvement in the quality of life of the whole people,residents’ needs for modern smart communities are becoming stronger and stronger.Under such social conditions,it is necessary to research and develop the prevention and control system of smart communities.Through investigation,Researched and determined the specific requirements of the system,And taking into account the current epidemic prevention and control work in the community.combined with face detection related algorithms to study the recognition model of non-standard mask wearing.Based on this,Researched and developed a smart community security system based on face detection.The main work done in this paper is as follows:First,in response to the current community epidemic prevention and control work,a recognition model for non-standard mask wearing is proposed.The model is composed of the face(mask wearing)detector Pyramid Box-MCCATT and the YCr Cb elliptical skin color model.The former is improved on the basis of Pyramid Box.First,Use clahe image preprocessing algorithm to solve the problem of low image quality.secondly,the attention mechanism based on multi-channel context is proposed to improve Pyramid Box.The context-sensitive prediction module in,improves the accuracy of face detection(wearing a mask).The latter converts the face image into a grayscale image of the skin,and analyzes the exposure of the mouth and nose based on this,and then judges whether to wear a mask in a standard manner.Experimental results show that the m AP detected by the face(wearing a mask)reaches 92.35%,and the recognition rate of irregular mask wearing reaches 89%.Second,designed a smart community security system based on the Spring Boot framework and Vue.js architecture.First,complete the summary analysis of the system requirements,and then clarify the detailed requirements;secondly,The system design mainly did two aspects of architecture design and database design.The main functions of the system include: 1)face query,face comparison,and establishment of a safety barrier at the community entrance control point;2)personnel and vehicle information management,which enables users to manage the community efficiently and conveniently;3)irregular masks are worn Identify and detect the irregular wearing of masks within the community.