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Simple Example: Clustering Images Using Expectation Maximization.

Authors :
Nakamura, Kurie
Kutics, Andrea
Nakagawa, Akihiko
Source :
2013 International Conference on Signal-Image Technology & Internet-Based Systems; 2013, p1071-1076, 6p
Publication Year :
2013

Abstract

This paper gives an example of a novel simple implementation of the EM algorithm for clustering images. Here we use a simple gray scale color feature to describe an image. When compared to results of other methods using the same simple feature, we found that the proposed method performs well. These comparison results imply that this simple model can be extended to cluster images using more complex features such as texture, shape, and other color descriptors to further improve the precision and recall of the results in order to outperform the existing methods. Further research can prove that this simplified EM algorithm achieves robust classification of unrestricted image domain. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISBNs :
9781479932115
Database :
Complementary Index
Journal :
2013 International Conference on Signal-Image Technology & Internet-Based Systems
Publication Type :
Conference
Accession number :
94540769
Full Text :
https://doi.org/10.1109/SITIS.2013.172