Shape descriptors based on tensor scale

Workshop of Theses and Dissertations, XXI Brazilian Symposium on Computer Graphics and Image Processing (WTD/SIBGRAPI), Campo Grande, MS, Brazil, 2008

Abstract

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. We exploit this concept for binary images and propose two shape descriptors – Tensor Scale Descriptor with Influence Zones and Tensor Scale Contour Saliences. 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 with regard to their use in content-based image retrieval tasks.

BibTeX

@inproceedings{andalo08sibgrapi,
    authors      = “Fernanda A. Andal{\‘o} and Ricardo da S. Torres and Alexandre X. Falc{~a}o”,
    title        = “Shape descriptors based on tensor scale”,
    booktitle    = “Workshop of Theses and Dissertations, {XXI} Brazilian Symposium on Computer Graphics and Image Processing ({WTD/SIBGRAPI})”,
    year         = 2008,
    address      = “Campo Grande, MS, Brazil”,
}