Title :
Local image descriptor based on spectral embedding
Author :
Pu Yan ; Jun Tang ; Ming Zhu ; Dong Liang
Author_Institution :
Sch. of Electron. & Inf. Eng., Anhui Univ., Hefei, China
Abstract :
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.
Keywords :
graph theory; image processing; JPEG compression; big curvature; edge point; illumination change; image blurring; image corner; image edge; image rotation; line graph spectra; linear intensity change; local image descriptor; noise robustness; rotation invariant image descriptor; spectral embedding; viewpoint change;
Journal_Title :
Computer Vision, IET
DOI :
10.1049/iet-cvi.2014.0124