Tetrakis square tiling-based triangulated feature descriptor aiding shape retrieval

摘要

Ongoing research addressing shape retrieval render highly acute feature descriptors that are computationally intensive. Hence, a simple approach through a novel tessellated version of the Tetrakis square tiling for acute feature characterization aiding shape retrieval is contributed in this paper. The proposed descriptor, named Triangulated Feature Descriptor (TFD), performs feature characterization and abstraction by fusing hybrid geometrical concepts. The mechanism initially tiles the image into square regions that are later tessellated into right-angled triangles. The right-angled triangular neighbors interact locally using the trigonometric identities to produce an angle-based feature map representing an image. The attained feature maps are locally segmented to finally produce a shape histogram. Since, the intended descriptor is modeled based on intrinsic angular interactions between the local neighbors the resulting descriptor is highly invariant to diverse affine transformations. This characteristic is examined by performing rigorous experiments on MPEG-7, TARI-1000, Articulated and PHOS datasets. Competitive analysis reveals a consistent retrieval rate greater than 85% achieved by TFD with increased performance scores. (C) 2018 Elsevier Inc. All rights reserved.