Robust Image Corner Detection Through Curvature Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Analysis and Classification: Theory and Practice
Shape Analysis and Classification: Theory and Practice
Digital Image Processing
BAS: a perceptual shape descriptor based on the beam angle statistics
Pattern Recognition Letters
The Image Foresting Transform: Theory, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
TSD: A Shape Descriptor Based on a Distribution of Tensor Scale Local Orientation
SIBGRAPI '05 Proceedings of the XVIII Brazilian Symposium on Computer Graphics and Image Processing
A graph-based framework for thermal faceprint characterization
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
Circle detection using electro-magnetism optimization
Information Sciences: an International Journal
Computer Vision and Image Understanding
Aquatic weed automatic classification using machine learning techniques
Computers and Electronics in Agriculture
Feature selection from high-order tensorial data via sparse decomposition
Pattern Recognition Letters
Tensor scale: An analytic approach with efficient computation and applications
Computer Vision and Image Understanding
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Tensor scale is a morphometric parameter that unifies the representation of local structure thickness, orientation, and anisotropy, which can be used in several computer vision and image processing tasks. In this article, we exploit this concept for binary images and propose a shape salience detector and a shape descriptor-Tensor Scale Descriptor with Influence Zones. It also introduces a robust method to compute tensor scale, using a graph-based approach-the Image Foresting Transform. Experimental results are provided, showing the effectiveness of the proposed methods, when compared to other relevant methods, such as Beam Angle Statistics and Contour Salience Descriptor, with regard to their use in content-based image retrieval tasks.