基于Co/sub /激光雷达图像的目标自动识别并行算法

D. Sullivan, A. Forman
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引用次数: 0

摘要

描述了一种从激光雷达图像中实现视点不变目标识别的并行算法。所使用的主动/被动CO/sub 2/激光雷达传感器提供像素注册的热、视觉、相对距离和伪影,并检测边缘。利用傅里叶变换的平移不变性得到视点不变性,将二维旋转和尺度变化转换为平移。这种场景表示提供了2-D视点不变性,并被用作神经网络的输入,该神经网络已被训练以识别感兴趣目标的代表性视图。该系统是在几何算术并行处理器(GAPP)上实现的,GAPP是一种大规模并行单指令多数据(SIMD)计算机,包含216*384数组的处理元素。给出了对真实激光雷达图像进行处理的结果
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Parallel algorithms for automatic target recognition using Co/sub 2/ laser radar images
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.<>
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