Image analysis for object detection in millimetre-wave images

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.