利用模糊形态学和规则对雷达场景进行描述

J. Keller, P. Gader, Xiaomei Wang
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引用次数: 11

摘要

提出了一种用激光雷达(LADAR)采集的数字图像自动生成场景描述的方法。提出了一种将场景与语言描述相匹配的方法。这两种方法都依赖于模糊空间关系。使用模糊数学形态学计算对象之间的原始空间关系,并与先前基于训练神经网络来学习人类偏好的方法进行比较。对于场景中的每对对象,使用模糊规则库将原始空间关系组合成复杂空间关系。使用最高置信度规则输出生成场景描述。使用与语言描述相对应的规则的输出执行场景匹配。结果表明,空间关系定义上看似显著的差异对系统性能影响不大,模糊系统可以生成合理的匹配分数和描述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
LADAR scene description using fuzzy morphology and rules
This paper presents a method for automatically generating descriptions of scenes represented by digital images acquired using laser radar (LADAR). A method for matching the scenes to linguistic descriptions is also presented. Both methods rely on fuzzy spatial relations. Primitive spatial relations between objects are computed using fuzzy mathematical morphology and compared to a previous method based on training a neural network to learn human preferences. For each pair of objects in a scene, the primitive spatial relations are combined into complex spatial relations using a fuzzy rule base. A scene description is generated using the highest confidence rule outputs. Scene matching is performed using the outputs of the rules that correspond to the linguistic description. The results show that seemingly significant differences in spatial relationship definitions have little impact on system performance and that reasonable match scores and descriptions can be generated from the fuzzy system.
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