Local image descriptor based on spectral embedding

This study presents a local image descriptor based on spectral embedding. Specifically, the spectra of line graph are used to represent image edges, corners and edge points with big curvature. The authors theoretically analyse and experimentally verify that the spectra of line graph are robust to no...

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Bibliographic Details
Main Authors: Pu Yan, Jun Tang, Ming Zhu, Dong Liang
Format: Article
Language:English
Published: Wiley 2015-04-01
Series:IET Computer Vision
Subjects:
Online Access:https://doi.org/10.1049/iet-cvi.2014.0124
Description
Summary:This study presents a local image descriptor based on spectral embedding. Specifically, the spectra of line graph are used to represent image edges, corners and edge points with big curvature. The authors theoretically analyse and experimentally verify that the spectra of line graph are robust to noise and are invariant to rotation and linear intensity changes. Based on such a fact, some local image descriptors are constructed using the spectra of line graph. Comparative experiments demonstrate the effectiveness of the proposed descriptor and its superiority to some state‐of‐the‐art descriptors under image rotation, image blur, viewpoint change, illumination change, JPEG compression and noise.
ISSN:1751-9632
1751-9640