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Image Classification using Statistical Learning Methods

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DOI: 10.4236/jsea.2012.512B038    4,225 Downloads   5,898 Views   Citations


In general, digital images can be classified into photographs, textual and mixed documents. This taxonomy is very useful in many applications, such as archiving task. However, there are no effective methods to perform this classification automatically. In this paper, we present a method for classifying and archiving document into the following semantic classes: photographs, textual and mixed documents. Our method is based on combining low-level image features, such as mean, Standard deviation, Skewness. Both the Decision Tree and Neuronal Network Classifiers are used for classification task.

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The authors declare no conflicts of interest.

Cite this paper

J. Mtimet and H. Amiri, "Image Classification using Statistical Learning Methods," Journal of Software Engineering and Applications, Vol. 5 No. 12B, 2012, pp. 200-203. doi: 10.4236/jsea.2012.512B038.


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