Image Classification using Statistical Learning Methods

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.

DOI: 10.4236/jsea.2012.512B038                

Abstract

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.

Keywords

Image classification; Decision Tree; Neuronal Network; statistical analysis

Conflicts of Interest

The authors declare no conflicts of interest.

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