1 research outputs found
A Riemanian Approach to Blob Detection in Manifold-Valued Images
This paper is devoted to the problem of blob detection in manifold-valued
images. Our solution is based on new definitions of blob response functions. We
define the blob response functions by means of curvatures of an image graph,
considered as a submanifold. We call the proposed framework Riemannian blob
detection. We prove that our approach can be viewed as a generalization of the
grayscale blob detection technique. An expression of the Riemannian blob
response functions through the image Hessian is derived. We provide experiments
for the case of vector-valued images on 2D surfaces: the proposed framework is
tested on the task of chemical compounds classification.Comment: Published in GSI 2017 proceeding