Author(s)

Jassem Mtimet, Hamid Amiri

Signal, Image and Technology of Information Laboratory, National Engineering School of Tunis, Tunis El Manar University, BP 37, Le Belvdre 1002, Tunis, Tunisia.

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.

Image classification; Decision Tree; Neuronal Network; statistical analysis

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.