Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
Baghdad Science Journal
View Archive Info| Field | Value | |
| Title |
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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| Creator |
Journal, Baghdad Science
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| Description |
Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.
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| Publisher |
College of Science for Women - University of Baghdad
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| Date |
2011-06-12
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion Peer-reviewed Article |
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| Format |
application/pdf
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| Identifier |
http://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/2553
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| Source |
مجلة بغداد للعلوم; مجلد 8 عدد 2 (2011): issue 2 المؤتمر العلمي الاول لقسم الفيزياء; 602-606
Baghdad Science Journal; Vol 8 No 2 (2011): issue 2 المؤتمر العلمي الاول لقسم الفيزياء; 602-606 2411-7986 2078-8665 |
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| Language |
eng
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| Relation |
http://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/2553/2484
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| Rights |
Copyright (c) 2011 Baghdad Science Journal
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