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Real time edge detected advanced image acquisition system using RGB analysis

机译:实时边缘检测使用RGB分析的高级图像采集系统

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In modern era the real time edge detection of moving elements in image sequences is the most important step in many image & video acquisition systems including automated visual surveillance. In this paper, we present an advanced framework for detecting some very important issues, like people identification and people flow count in restricted organizations for security measures. The objectives is to constant monitor activities at restricted regions for detecting unwanted congestions and predict the people flow which assists in regulating the crowd density at the target place. This unique approach help us as the system can sense the frame of target object, detect instantly the edges of the target, automatically process the captured footage and provides the filtered version of the target image/video. In addition with, our proposed system can also track the motion of the target object (people). Also color histograms (RGB) help us to make prompt decisions while capturing the total range of existing digital image/video. In this paper the proposed system with such modern features combined is designed using MAT Lab/SIMULINK V.7.10.0 and simulated. The related experimental results are shown and evaluated successfully.
机译:在现代时代,图像序列中移动元件的实时边缘检测是许多图像和视频采集系统中最重要的步骤,包括自动视觉监视。在本文中,我们提出了一个用于检测一些非常重要的问题的先进框架,如人们的识别和人们在受限制组织的安全措施中计数。目标是在限制区域持续监测活动,以检测不需要的拥堵,并预测人们有助于调节目标位置的人群密度。这种独特的方法可以帮助我们随着系统可以感知目标对象的帧,立即检测目标的边缘,自动处理捕获的素材并提供目标图像/视频的过滤版本。此外,我们的建议系统还可以跟踪目标对象(人)的运动。颜色直方图(RGB)帮助我们在捕获现有数码图像/视频的总范围的同时进行提示决策。在本文中,组合使用此类现代功能的提议系统使用MAT Lab / Simulink V.7.10.0和模拟设计。相关实验结果显示并成功地评估。

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