Injury Identification Using Video Magnification

Mohamad Alansari, Wessam Shehieb, Sara Alansari, Ayman Tawfik
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引用次数: 0

Abstract

Despite the rapid technological advancements and developments that are achieved today, correct injuries diagnose is still a regular occurring issue. There are many methods to diagnose and determine injuries, but these methods are expensive and time consuming. In this work, a portable smartphone-based video magnification (VM) technique and machine learning algorithm Haar Cascade are used to detect injuries. The main objective of this work is to develop a worldwide accessible application that detects injuries in real-time manner using video magnification of the blood’s colour circulated through the injured body part. The blood flow rate is used because since injuries directly cause an increase in blood flow rate. The proposed system was successfully implemented with accuracy of 95.07%.
使用视频放大识别损伤
尽管今天技术进步和发展迅速,但正确的损伤诊断仍然是一个经常发生的问题。有许多方法可以诊断和确定损伤,但这些方法既昂贵又耗时。在这项工作中,使用基于便携式智能手机的视频放大(VM)技术和机器学习算法Haar Cascade来检测损伤。这项工作的主要目标是开发一种全球可访问的应用程序,该应用程序通过视频放大在受伤身体部位循环的血液颜色,实时检测损伤。使用血流量是因为损伤会直接导致血流量的增加。该系统成功实现,准确率为95.07%。
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