通过热成像验证特征检测:PiBase的扩展

Anthony Atkinson, Venkat Margapuri, Michael L. Neilsen
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引用次数: 0

摘要

PiBase是一款低成本、具有物联网功能的安全系统。它为用户提供了一个硬件和软件的集成系统,包括一个由树莓派和现成部件制成的基本智能摄像头、一个安卓应用程序和一个为谷歌Firebase构建的后端。使用haar特征级联分类器和线性二进制模式直方图,它试图提供对潜在安全威胁的全面检测和识别。作为一个原型,在初始设计中存在一些漏洞。这种新设计解决了一个安全威胁,即模仿授权用户外观的可能性。这是通过将热成像与系统中使用的原始相机集成来实现的。这种方法的一些挑战包括保持低成本和部件可及性,在硬件的限制下工作,以及选择有效的集成方法。除了原始问题之外,提出的解决方案还解决了这些问题,通过将低分辨率热传感器阵列的输出转换为一种剪切掩模,在执行其他操作之前从输入图像中滤除非人类物体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Verification of Feature Detection Through Thermal Imaging: An Extension of PiBase
PiBase is a low-cost, Internet-of-Things-capable security systems. It offers users an integrated system of hardware and software in the form of a basic smart camera made from a Raspberry Pi and off-the-shelf parts, an Android app, and a backend built for Google Firebase. Using Haar-feature cascade classifiers and Linear Binary Pattern Histograms, it attempts to provide comprehensive detection and recognition of potential security threats. Being only a prototype there are some vulnerabilities in the initial design. This new design addresses one security threat, namely the possibility of mimicking an authorized user’s appearance. This is achieved through the integration of thermal imaging alongside the original camera used in the system. Some challenges with this approach include maintaining low-cost and part accessibility, working within limitations of the hardware, and choosing an effective method of integration. The proposed solution addresses each of these, in addition to the original issue, by transforming the output of a low-resolution thermal sensor array into a kind of clipping-mask to filter out non-human objects from the input image before performing its other operations.
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