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An experimental study on object recognition and enhancement in MWIR thermography

机译:MWIR热成像中目标识别与增强的实验研究

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摘要

An infrared (IR) camera is one of the common tools for taking images for thermography analysis in the medical field. In this paper, object recognition using infrared images captured with a middle wave infrared (MWIR) camera is studied. By using the InSb detector, the MWIR system used in this study operates in the 3-5 μm waveband, and it is well-suited for high-end research and development applications. To enhance the applicability of MWIR thermography to medical-related problems, it is important to devise reliable recognition and enhancement techniques for MWIR images. In this work, an experimental study is conducted to identify the capability of MWIR thermography in distinguishing an object (a human hand) from its background with varying emissivity and temperature levels. It is observed that object recognition becomes difficult when the emissivity difference is within 0.01 under the temperature condition of within 1℃ for the object and the background. In addition, a histogram equalisation approach is utilised to enhance blurry images from the MWIR system. The results demonstrate the histogram equalisation method is able to expand the dynamic range expansion of image grey levels so that the output image becomes clear and visible for object recognition.
机译:红外(IR)摄像机是医学领域中用于热成像分析的常用图像采集工具之一。在本文中,研究了使用中波红外(MWIR)摄像机捕获的红外图像进行目标识别。通过使用InSb检测器,本研究中使用的MWIR系统在3-5μm波段内运行,非常适合高端研发应用。为了提高MWIR热成像技术在医疗相关问题上的适用性,重要的是为MWIR图像设计可靠的识别和增强技术。在这项工作中,进行了一项实验研究,以确定MWIR热成像技术在具有不同发射率和温度水平的物体(人手)与背景之间的区别。可以看出,在1℃以内的温度条件下,对于物体和背景,当发射率差在0.01以内时,物体识别变得困难。另外,利用直方图均衡方法来增强来自MWIR系统的模糊图像。结果表明,直方图均衡化方法能够扩展图像灰度级的动态范围扩展,从而使输出图像变得清晰可见,以进行对象识别。

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