DocumentCode
248416
Title
A complex network based feature extraction for image retrieval
Author
Jieqi Kang ; Shan Lu ; Weibo Gong ; Kelly, P.A.
Author_Institution
Electr. & Comput. Eng. Dept., Univ. of Massachusetts, Amherst, MA, USA
fYear
2014
fDate
27-30 Oct. 2014
Firstpage
2051
Lastpage
2055
Abstract
In this paper, we propose a complex network based low-level feature for image retrieval systems based on the graph representation of the image and the mathematical theory of diffusion over manifolds. We show that the proposed image feature is invariant to non-structural changes on images and performs well in hand written digits classification task. We also show that performance of image retrieval with existing low-level features could be improved by combining with the proposed feature.
Keywords
complex networks; content-based retrieval; feature extraction; graph theory; handwritten character recognition; image classification; image representation; image retrieval; complex network based feature extraction; graph representation; hand written digit classification task; image retrieval systems; low-level feature system; mathematical diffusion theory; nonstructural changes; Feature extraction; Heating; Histograms; Image edge detection; Image retrieval; Laplace equations; Spectrogram;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location
Paris
Type
conf
DOI
10.1109/ICIP.2014.7025411
Filename
7025411
Link To Document