Active/passive cooperative image segmentation for automatic target recognition

Jean-Yves Dufour; Vincent Martin

doi:10.1117/12.186569

21 September 1994 Active/passive cooperative image segmentation for automatic target recognition

Jean-Yves Dufour, Vincent Martin

Proceedings Volume 2298, Applications of Digital Image Processing XVII; (1994) https://doi.org/10.1117/12.186569
Event: SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, 1994, San Diego, CA, United States

Abstract

This paper deals with the fusion of data delivered by an active LIDAR (light detection and ranging) sensor and a passive FLIR sensor, in the framework of ground-to-ground automatic target recognition (ATR). ATR operators usually analyze features which are measurements of the observed object. Recognition process efficiency highly depends on both variety and stability of these features. Active/passive fusion clearly provides a large amount of miscellaneous data. It is shown here that it can also greatly improve target silhouette extraction and thus increase the stability of morphological features. Target silhouette extraction is performed by an image segmentation algorithm which analyzes LIDAR and FLIR registered images. The main stages of the algorithm are described. Experimental results obtained by processing outdoor scene data are presented.

Citation Download Citation

Jean-Yves Dufour and Vincent Martin "Active/passive cooperative image segmentation for automatic target recognition", Proc. SPIE 2298, Applications of Digital Image Processing XVII, (21 September 1994); https://doi.org/10.1117/12.186569

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