Abstract
This paper presents an automatic target recognition (ATR) system for laser radar (LADAR) imagery, designed to classify objects at multiple levels of discrimination (target detection, classification, and recognition) from single LADAR images. Segmentation is performed in both the range and non-range LADAR channels and results combined to increase object detection rate or decrease false positive detection rate. Through use of the range data, object subimages are projected and rotated to canonical orientations, providing invariance to translation, scale and rotations in 3-D. Global features are extracted for rapid target detection and local receptive field features are computed for target recognition 100% detection and recognition rates are shown for a small set of real LADAR data.
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