Shape recognition and retrieval: A structural approach using velocity function

Abstract

In this paper a new method for matching and recognition of shapes extracted from images, based on the structure and skeleton of the shape, is proposed. In this method, a function called "velocity function" derived from the radius function is introduced and values of this function are calculated for skeletal points. At this point, each skeletal curve is transformed into a vector containing values of the velocity function calculated along the curve. Then a tree-like structure is extracted from the skeleton of the shape so that each leaf of the tree indicates a skeletal curve of the skeleton and a velocity vector as its descriptor. These vectors are matched in fine-grain level using dynamic programming method and in coarse-grain level, the tree-like structures are matched using a greedy approach. At the final stage, the difference between the shapes is determined by a distance value resulted from the two levels matching process. This distance is used as a measure for shape matching and recognition. Experiments are performed on two standard binary image database in the presence of various transformations. Results confirm the efficiency and high recognition rate of our method. © Springer-Verlag Berlin Heidelberg 2007.