Region-based shape descriptor invariant to rotation, scale and translation
A region-based shape descriptor invariant to rotation, scale and translation is presented in this paper. For a given binary shape, positions of pixels belonging to the shape are regarded as observed vectors of a 2-D random vector and two eigenvectors are obtained from the covariance matrix of the vector population. The shape is divided into four sub-regions by two principal axes corresponding to the two eigenvectors at the center of mass of the shape. Each sub-region is subdivided into four sub-regions in the same way. The sub-division process is repeated for a predetermined number of times. A quadtree representation with its nodes corresponding to regions of the shape is derived from the above process. Four parameters invariant to translation, rotation and scale are calculated for the corresponding region of each node while two parameters are extracted for the root node. The shape descriptor is represented as a vector of all the parameters and the similarity distance between two shapes is calculated by summing up the absolute differences of each element of descriptor vectors. Experimental results conforming to the MPEG-7 shape descriptor core experiments are presented.
shape descriptor similarity mpeg-7 image retrieval transformation invariant