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Intelligent hyper-spectral mm-wave illumination techniques for feature extraction of hidden objects in indoor security applications: a fusion of photonics, electronics and electromagnetism Host Publication: Work shop of the International Symposium of MicroWave Photonics, Gold Coast (australia), 30Sep-3Oct 2008 Authors: J. Stiens Publication Date: Sep. 2008
Abstract: In recent years the research field of mm waves, the spectral band between 30 and 300 GHz has expanded in security and biomedical applications, because mm-waves yield a convenient compromise between acceptable resolution and sufficient penetration depth through a variety of materials, non-transparent in the visible. E.g. mm waves penetrate clothing to image concealed weapons, but also allow skin cancer detection and skin wound healing assessment. In indoor applications the temperature contrast between the body, objects under investigation and the background of the scene (walls of a room or hall) is too low for making high contrast imaging in a reasonable exposure time. Active imaging techniques can outperform passive systems in contrast and resolution when the typical image artifacts inherent to active systems are understood and can be eliminated.
In this paper we focus on security applications in the W-band (75뀶 GHz) Illuminating the object in the mm-wave band is not obvious due to the lack of the equivalent of a "classic" flash lamp. On the contrary one needs to cope with coherent illumination sources such as Gunn or Impatt diodes or BWOs, resulting in a series of typical coherent specific image artifacts such as speckle, ringing, glint and interferometric noise, ... In this paper we will show how the disadvantages of coherent illumination can be converted in more favorable conditions for image improvement and material or pattern recognition. We will discuss the issues related to the system design and related electromagnetic simulations, the antenna coupled devices and technological implementations. Finally, the parameters of the multidimensional illumination set will be discussed: multi-angle, multi-frequency, multi-polarization and multi-phase patterns. Afterwards the various multi-dimensional arrays of mm wave images will be analyzed and correlated with each other to distinguish between different materials (metals, dielectrics, depolarizing materials). We will apply and adapt various common image processing techniques and reconstruction algorithms. Different examples specific to security applications will be discussed in detail.
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