Simple Example: Clustering Images Using Expectation Maximization

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.