陨石坑自动识别的特征提取算法

N. Christoff
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引用次数: 0

摘要

摘要:近年来,特征选择算法得到了广泛的研究。利用三维数据绘制特征,自动分类识别弹坑。这也将有助于文本分类器的性能。在这项工作中,我们的目的是通过在灰度范围内转换最小曲率的原始值(以下称为“纯”值)来观察它们的判别能力。我们对系统进行了测试,发现五种不同的分类器对从灰度图像中选择的特征获得了更好的准确率结果。我们还发现,计算机视觉方法也适用于弹坑检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Feature Extraction Algorithms for Automatic Craters Identification
1 ABSTRACT: Recently the feature selection algorithms are extensively studied. Using 3D data, the features are drawn for automatic classification and identify craters. This will also help to text the performance of the classifiers. Our intention in this work is to observe the discriminative power of the original values, hereafter called “pure” values, of a minimal curvature by only converting them in the range of grey scale. We have tested the system and found that the five different classifiers show that better accuracy results are obtained over the features selected from the grey scale image. We also found that the method from computer vision is applied for the crater detection.
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