IMAGE AND SHAPE COMPARISON VIA MORPHOLOGICAL CORRELATION

Abstract. A lot of image matching applications require image comparison to be invariant relative to intensity values variations. The Pyt’ev theory for Morphological Image Analysis (MIA) was developed based on image-to-shape matching with mosaic shape models. Within the framework of this theory, the problem of shape-to-shape comparison was previously considered too. The most sophisticated and weakest part of MIA theory is the comparison of mosaic shapes with some arbitrary restrictions described by graphs or relations. In this paper we consider the possible options for comparing images and shapes using morphological projection and morphological correlation. Our contribution is a new scheme of morphological shape-to-image projection and, correspondingly, the new morphological correlation coefficient (MCC) for shape-to-image correlation with restricted mosaic models. We also refine the expressions for shape-to-shape comparison.