Feature Extraction Algorithms for Automatic Craters Identification
Nicole Christoff
Journal of Multimedia Processing and Technologies, Vol. 12, No. 1, 2021.
DOI: https://doi.org/10.6025/jmpt/2021/12/1/1-8
Link: https://www.dline.info/jmpt/fulltext/v12n1/jmptv12n1_1.pdf
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 â€œpureâ€ 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.