Concealed object detection with radiometric imaging

Concealed object detection with radiometric imaging

A passive millimeter wave imaging system can detect concealed objects under clothing. In this paper, we address realtime outdoor concealed-object detection and segmentation with a radiometric imaging system. The radiometric imaging system operates around 94 GHz to generate images with a 1 Hz frame r...

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Bibliographische Detailangaben
Hauptverfasser: Seokwon Yeom, Dong-Su Lee, Jung-Young Son, Min-Kyoo Jung, Yushin Jang, Sang-Won Jung, Seok-Jae Lee
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Bayesian methods
Clustering algorithms
concealed object detection
Fitting
Gaussian mixture modeling
Image segmentation
Imaging
Millimeter wave radar
passive millimeter
unsupervised learing
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Zusammenfassung:A passive millimeter wave imaging system can detect concealed objects under clothing. In this paper, we address realtime outdoor concealed-object detection and segmentation with a radiometric imaging system. The radiometric imaging system operates around 94 GHz to generate images with a 1 Hz frame rate. Multilevel segmentation clusters pixels according to a Gaussian mixture model. Experimental results confirm that the presented method can recognize a concealed gun carried by a moving human subject.