Parallel algorithms for automatic target recognition using Co/sub 2/ laser radar images

Abstract

A parallel implementation of algorithms to achieve viewpoint invariant target recognition from laser radar images is described. The active/passive CO/sub 2/ laser radar sensor used provides pixel-registered thermal, visual, relative range and artifacts and detects edges. Viewpoint invariance obtained using the translation invariant property of the Fourier transform transforms 2-D rotations and scale changes into translations. This scene representation provides 2-D viewpoint invariance and is used as input to a neural network that has been trained to recognize representative views of the targets of interest. The system is implemented on the Geometric Arithmetic Parallel Processor (GAPP), a massively parallel single-instruction-multiple-data (SIMD) computer that contains a 216*384 array of processing elements. Results obtained by processing real lasers radar images are presented.<>