Edge based Crime Assistance System with Cloud Computing

Khin Myint Myat Thu, N. Thein
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引用次数: 1

Abstract

Nowadays, the level of crime is increasing more and more in every corner of the world. With the rising rate of criminal activities, the identification process of the person who committed crime takes a lot of time. Most of the crime reporting systems currently are reported personally. In order to create a fast and reliable crime reporting system, the face identification in crime assistance system between edge and cloud computing is proposed. The processing power of ubiquitous devices (e.g. smartphones, sensors, and actuators) are very powerful today. They allow capturing the image of the criminal anywhere at any time. They also have the capability of detecting faces from captured image. Therefore, the face detection process using Haar face detection and face identifier generation process using Local Binary Pattern (LBP) from the captured image can take place on the edge devices. Face identifier matching is proceeded on the cloud. The paper proposed the edge-based face identification system and represents the analysis result of face detection time, matching time and total processing time of the proposed system with the increasing number of test image data set. The results show the effective usage of edge devices and improve the efficiency of face identification.
基于边缘的犯罪辅助系统与云计算
如今,犯罪的水平在世界的每个角落都越来越多。随着犯罪活动的增加,对犯罪人员的识别过程需要花费大量的时间。目前大多数的犯罪报告系统都是亲自报告的。为了创建一个快速可靠的犯罪报告系统,提出了边缘计算与云计算相结合的犯罪辅助系统中的人脸识别。如今,无处不在的设备(如智能手机、传感器和执行器)的处理能力非常强大。它们可以随时随地捕捉罪犯的图像。它们还具有从捕获的图像中检测人脸的能力。因此,使用Haar人脸检测的人脸检测过程和使用局部二值模式(LBP)从捕获的图像中生成人脸标识符的过程可以在边缘设备上进行。人脸识别匹配在云端进行。本文提出了基于边缘的人脸识别系统,并表示了随着测试图像数据集数量的增加,所提出系统的人脸检测时间、匹配时间和总处理时间的分析结果。结果表明,边缘设备的有效利用提高了人脸识别的效率。
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