Texture retrieval using co-occurrence matrix and symbolic interval data under scale and rotation invariance

This article presents a new method for texture description suitable to be used as a solution to the retrieval problem in large image collections. The proposed approach combines multiscalegray-level co-occurrence matrices (GLCM) with Symbolic Data Analysis. A benchmark data set is used to demonstrate the usefulness of the proposed methodology. The experimental results demonstrate that the proposed method is encouraging with an average successful rate of 100% for Dataset 1 and 97.9% for Dataset 2.