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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

TSS & TSB: Tensor scale descriptors within circular sectors for fast shape retrieval

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Author(s):
Freitas, Anderson M. ; Torres, Ricardo da S. ; Miranda, Paulo A. V.
Total Authors: 3
Document type: Journal article
Source: PATTERN RECOGNITION LETTERS; v. 83, n. 3, p. 303-311, NOV 1 2016.
Web of Science Citations: 4
Abstract

We propose two novel region-based descriptors for shape-based image retrieval and analysis, which are built upon an extended tensor scale based on the Euclidean Distance Transform (EDT). First the tensor scale algorithm is applied to extract local structure thickness, orientation, and anisotropy as represented by the largest ellipse within a homogeneous region centered at each image pixel. In this work, we extend the local orientation to 360 degrees. Then, for the first proposed descriptor, named Tensor Scale Sector descriptor (TSS), the local distributions of relative orientations within circular sectors are used to compose a fixed-length feature vector for a region-based representation. For the second method, named Tensor Scale Band descriptor (TSB), we consider histograms of relative orientations for each circular concentric band to compose a fixed-length feature vector with linear time matching. Experimental results with MPEG-7 and MNIST datasets are presented to illustrate and validate the methods. TSS can achieve high retrieval values comparable to state-of-the-art methods, which usually rely on time-consuming correspondence optimization algorithms, but uses a simpler and faster distance function, while the even faster linear complexity of TSB leads to a suitable and better solution for very large shape collections. (C) 2016 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 11/50761-2 - Models and methods of e-Science for life and agricultural sciences
Grantee:Roberto Marcondes Cesar Junior
Support type: Research Projects - Thematic Grants