Image Categorization Using Improved Data Mining Technique

Abstract

Image categorization is one of the important branches of artificial intelligence. Categorization of images is a way of grouping images according to their similarity. Image categorization uses various features of images like texture, color component, shape, edge, etc. Categorization process has various steps like image preprocessing, object detection, object segmentation, feature extraction, and object classification. For the past few years, researchers have been contributing different algorithms in the two most common machine learning categories to either cluster or classify images. The goal of this paper is to discuss two of the most popular machine learning algorithms: Nearest Neighbor (k-NN) for image classification and Means clustering algorithm. After that, a Hybrid model of both the above algorithms is proposed. These algorithms are implemented in MATLAB; finally, the experimental results of each algorithm are presented and discussed.