Hexagonal Grid based triangulated feature descriptor for shape retrieval

摘要

Shape characterization schemes catering object recognition and retrieval have been undergoing intense study in computer vision. As shape encompasses much of image information, yielding higher retrieval performance with less complexity continues to be a challenging issue. Accordingly, a simple approach, blending hexagonal grid modelling with triangular tessellation for shape matching and retrieval is proposed in this paper. At the onset, a shape image is decomposed into overlapping hexagonal grids that are then divided into six non-overlapping equilateral triangles. Next, the intensity differences of each triangle side is evaluated and the maximum of the three sides is retained. This process is repeated on the remaining triangles that produces six maximum values corresponding to each triangle. These six values, then replace the six corners of the hexagonal subregion to finally produce a feature map that is uniquely packed into feature histograms representing the given shape. Quantitative and qualitative examinations on MPEG-7, TARI-1000 and Kimia's 99 datasets reveals a consistent BER greater than 90%. The superior performance over its competitors can be attributed to the congruent nature of the hexagonal and triangular tessellation. (C) 2018 Elsevier B.V. All rights reserved.