Improved segmentation of meteorite micro-CT images using local histograms
Improved segmentation of meteorite micro-CT images using local histograms
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DOI：
10.1016/j.cageo.2011.07.002
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发表时间：
2012-02-01
影响因子：
4.4
通讯作者：
Hezel, D. C.
中科院分区：
文献类型：
--
作者：
Griffin, L. D.;Elangovan, P.;Hezel, D. C.
在陨石的显微CT图像中，单个成分，如基质，球粒，钙，富铝夹杂物（CAIs）和不透明相（金属和硫化物）在视觉上是可以区分的。对于三维CT图像中的大量数据，需要进行成分的自动分类。通过像素强度分类实现的性能只有从基线到完美的25%。差的性能是由不同组件中存在的强度范围的重叠解释的。提出了一种改进的基于局部灰度直方图的半自动分类方法。这实现了从基线到完美的60%的性能。(C)2011爱思唯尔有限公司版权所有。
In micro-CT images of meteorites individual components such as matrix, chondrules, Ca,Al-rich inclusions (CAIs), and opaque phases (metal and sulfide) are visually distinguishable. Automated classification of the components is desirable to deal with the large amount of data in a 3-D CT image. Classification by pixel intensity achieves a performance only 25% of the way from baseline to perfect. The poor performance is explained by an overlap in the range of intensities present in the different components. An improved method of semiautomated classification is presented, based on local histograms of the intensity. This achieves a performance 60% of the way from baseline to perfect. (C) 2011 Elsevier Ltd. All rights reserved.