Internet of Things Technology of Imagine Processing for Smart House

Valeriia Mykolaivna Okhmak, A. Krylov
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Abstract

The article considers the image processing, detection of human faces and the transfer of relevant information in MATLAB software. During the rapid global process of industrialization and globalization, elements of smart homes for personal use are becoming popular in production and offices. Life and personal information security is the most important requirement and task of current and future Internet of Things solutions. Therefore, the system of recognizing objects, including people, is relevant and still one that can be qualitatively improved.  The processing begins with a state file, which can be replaced by real-time systems, after receiving information from video — is selected in groups of points, which are the corresponding arrays of information. Arrays contains numbers which indicate whether a human face in front of the camera. The data is calibrated to avoid false detection with median distribution. As a result of involving graphic additions, the user can observe in real time where and how many faces are in front of the camera. MATLAB was chosen as the programming environment, because the program includes built-in blocks that allow you to easily combine the mathematical and applied part of the proposed solution. As a result of modeling a complex model was obtained that is able to process the image and determine the necessary elements and objects in the image. This model can be used to track changes in position in space, any, object or objects depending on their size or physical characteristics. A feature of the proposed method is the ability to calibrate and optimize the mathematical model depending on the physical parameters of the system and the required information at the output of the system.
面向智能家居的物联网图像处理技术
本文研究了在MATLAB软件中进行图像处理、人脸检测以及相关信息的传递。在全球快速工业化和全球化的进程中,个人使用的智能家居元素在生产和办公中越来越受欢迎。生活和个人信息安全是当前和未来物联网解决方案最重要的要求和任务。因此,识别物体(包括人)的系统是相关的,并且仍然是一个可以在质量上得到改进的系统。处理从一个状态文件开始,这个状态文件可以被实时系统替换,在接收到视频信息后,被选择在一组点中,这是相应的信息数组。数组包含数字,表明是否有人脸在相机前。对数据进行了校准,以避免中位数分布的误检。由于添加了图形,用户可以实时观察到相机前有多少张脸和在哪里。之所以选择MATLAB作为编程环境,是因为该程序包含内置模块,允许您轻松地将所提出的解决方案的数学和应用部分结合起来。建模的结果是得到了一个复杂的模型,该模型能够处理图像并确定图像中必要的元素和对象。该模型可用于根据物体的大小或物理特征跟踪空间中任何物体或物体的位置变化。该方法的一个特点是能够根据系统的物理参数和系统输出所需的信息校准和优化数学模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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