Image categorization using texture features

A method for finding all images from the same category as a given query image (termed `categorization´) using texture features is presented. The hypothesis that two images that are similar in texture are likely to belong to the same category is examined. A new texture feature called an N×M-gram is presented. It is based on the N-gram technique that is commonly used for text similarity. The process of computing an image profile in terms of its N×M-grams is described. Results of experiments on images from various categories are presented. The N×M-gram method with three different similarity measures is compared to the results of categorization using other well-known texture features and grey-level distribution features. The results show that, for our test images, texture features are suitable for image categorization, and N×M-gram based methods are the best overall choice of texture features for this task