Journal of Pattern Recognition Research

A 2-D shape description using the turning angle (or tangential angle) is presented . This representation is based on a scalogram obtained from a progressive filtering of a planar closed contour of an object. At a given scale, one can calculate the differential turning angle function from which, three essential points are defined: the minimum differential-turning angle (a-points), the maximum differential-turning angle (b-points) and the zero-crossing of the turning angle (g-points). For a continuum of the scale values of the filtering process, a map (called d-TASS map) is generated. As shown experimentally in a previous study, this representation is invariant under rotation, translation and scale change. Moreover, it is shearing and noise resistant. The contribution of the present study is first, to prove theoretically that d-TASS is rotation and scale change invariant; then we propose a descriptor based on a feature matrix extracted from the blocks within the scalogram. When applied to shape retrieval from commonly used image databases like (MPEG-7 Core Experiments Shape-1 dataset, Multiview Curve Dataset and marines animals of SQUID dataset), experimental results yield very encouraging efficiency and effectiveness of the new analysis approach and the proposed descriptor.