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Feature Extraction of Asterias Amurensis by Using the Multi-Directional Linear Scanning and Convex Hull
Journal of The Korea Society of Computer and Information
Abbr :
JKSCI
2011, 16(3), pp.99-108
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science
2011, 16(3), pp.99-108
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science
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The feature extraction of asterias amurensis by using patterns is difficult to extract all the concave and convex features of asterias amurensis nor classify concave and convex. Concave and convex as important structural features of asterias amurensis are the features which should be found and the classification of concave and convex is also necessary for the recognition of asterias amurensis later. Accordingly, this study suggests the technique to extract the features of concave and convex, the main features of asterias amurensis. This technique classifies the concave and convex features by using the multi-directional linear scanning and form the candidate groups of the concave and convex feature points and decide the feature points of the candidate groups and apply convex hull algorithm to the extracted feature points. The suggested technique efficiently extracts the concave and convex features, the main features of asterias amurensis by dividing them. Accordingly, it is expected to contribute to the studies on the recognition of asterias amurensis in the future
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