Image Matching by Using Fuzzy Transforms

Abstract

We apply the concept of Fuzzy Transform (for short, F-transform) for improving the results of the image matching based on the Greatest Eigen Fuzzy Set (for short, GEFS) with respect to max-min composition and the Smallest Eigen Fuzzy Set (for short, SEFS) with respect to min-max composition already studied in the literature. The direct F-transform of an image can be compared with the direct F-transform of a sample image to be matched and we use suitable indexes to measure the grade of similarity between the two images. We make our experiments on the image dataset extracted from the well-known Prima Project View Sphere Database, comparing the results obtained with this method with that one based on the GEFS and SEFS. Other experiments are performed on frames of videos extracted from the Ohio State University dataset.