Maximally Stable Texture Regions

In this study, we propose to detect interest regions based on texture information of images. For this purpose, Maximally Stable Extremal Regions (MSER) approach is extended using the high dimensional texture features of image pixels. The regions with different textures from their vicinity are detected using agglomerative clustering successively. The proposed approach is evaluated in terms of repeatability and matching scores in an experimental setup used in the literature. It outperforms the intensity and color based detectors, especially in the images containing textured regions. It succeeds better in the transformations including viewpoint change, blurring, illumination and JPEG compression, while producing comparable results in the other transformations tested in the experiments.