A multisensor image analysis system that locates and recognizes realistic models of military objects placed on a terrain board has been demonstrated. Images are acquired using two overhead video sensors--a wide field, low resolution camera for cueing and a narrow field, high resolution camera for object segmentation and recognition. The red, green, and blue sensor information is fused and used in the digital image analysis. Small regions of interest located within the wide field-of-view scene by a high-speed digital cuer are automatically acquired and imaged by the high resolution camera. A high-speed statistical segmenter produces a binary image of any military object found within a given region and sends it to a computer-controlled binary phase-only optical correlator for recognition. Rotation, scale and aspect invariant recognition is accomplished using a binary tree search of composite binary phase-only filters. The system can reliably recognize any one of ten different objects placed at any location and orientation on the terrain board within ten seconds.
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