Affine morphological shape stable boundary regions (SSBR) for image representation
Petros Kapsalas, Stefanos Kollias · 2011
This paper presents a new structure-based interest region detector called Shape-Stable Region Boundaries (SSRB) which we use for object class recognition. The SSRB interest operator detects stable boundary regions within the multi-scale morphological image representation [1]. To detect robust boundary regions, we perform multi-scale analysis via anisotropic diffusion operators to preserve boundaries and guarantee invariance to affine transformations. We extract the transition boundaries of the diffusivity velocity map and track their evolution at each level of the scale-space. The stability of the boundary shape is subsequently estimated through a minimization process over different scales. Unlike most state of the art detectors which use the Gaussian scale space for multi-scale image representation, our approach is intrinsically affine invariant [1]. Experiments on different benchmark datasets show that SSRB is comparable or superior to state-of the art detectors for both feature matching and object recognition.