Implementation of intelligent healthcare image detection system based on OpenCV

Abstract

As an interface between image processing technology and the real world, image detection can achieve real-time capture of information such as images and movements. It has wide applications in fields such as medical rehabilitation, military simulation, and intelligent recognition. This article aims to achieve autonomous medical detection and assist doctors in diagnosis. Based on a detailed analysis of the principles of image detection technology and the current development status of image detection technology, a comprehensive medical detection system solution is designed. Addressing issues such as the tension of hospital registration queues, lengthy doctor-patient consultations, lack of auxiliary diagnostic functions, and non-visualizable diagnosis and treatment results, this study utilizes literature analysis and modeling to simulate the collection and intelligent analysis of surface images of the human body and limb movements. This enables the realization of functions such as image detection, image capture, image transmission, image processing, and medical feedback. This article has completed the design of an intelligent medical system, solving the problem of low medical diagnosis efficiency. At the same time, it has been found that the clarity of infrared thermal imaging images is not high, which affects the accuracy of collecting human surface images and limb movements. The processing of infrared thermal imaging images has become a direction that needs further research.