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Image Analysis for Object Detection in Millimetre-wave Images

机译:毫米波图像中对象检测的图像分析

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Video-frame-rate millimetre-wave imaging has recently been demonstrated with a quality similar to that of a low-quality uncooled thermal imager. In this paper we will discuss initial investigations into the transfer of image processing algorithms from more mature imaging modalities to millimetre-wave imagery. The current aim is to develop body segmentation algorithms for use in object detection and analysis. However, this requires a variety of image processing algorithms from different domains, including image de-noising, segmentation and motion tracking. This paper focuses on results from the segmentation of a body from the millimetre-wave images and a qualitative comparison of different approaches is presented. Their performance is analysed and any characteristics which enhance or limit their application are discussed. While it is possible to apply image processing algorithms developed for the visible-band directly to millimetre-wave images, the physics of the image formation process is very different. This paper discusses the potential for exploiting an understanding of the physics of image formation in the image segmentation process to enhance classification of scene components and, thereby, improve segmentation performance. This paper presents some results from a millimetre-wave image formation simulator, including synthetic images with multiple objects in the scene.
机译:最近已经证明了视频帧速率毫米波成像,其质量类似于低质量的未加工热成像仪。在本文中,我们将讨论从更成熟的成像方式转移到图像处理算法到毫米波图像的初步调查。目前的目的是开发用于物体检测和分析的体分割算法。然而,这需要来自不同域的各种图像处理算法,包括图像去噪,分段和运动跟踪。本文侧重于来自毫米波图像的体内分割的结果,并提出了不同方法的定性比较。分析了他们的表现,并讨论了任何增强或限制其申请的任何特征。虽然可以直接向毫米波图像应用于可见带开发的图像处理算法,但是图像形成过程的物理学非常不同。本文讨论了利用图像分割过程中图像形成物理物理学的可能性,以增强场景分量的分类,从而提高分割性能。本文介绍了毫米波图像形成模拟器的一些结果,包括场景中具有多个对象的合成图像。

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