DocumentCode
2977345
Title
Design Image Retrieval Based on Nonsubsampled Contourlet Transform and Neural Networks
Author
Li, Yi ; Liu, Guanzhong
Author_Institution
Bus. Sch., Central South Univ., Changsha, China
fYear
2011
fDate
12-14 Aug. 2011
Firstpage
1
Lastpage
4
Abstract
In this paper, an image retrieval method based on nonsubsampled contourlet transform (NSCT) is proposed. Firstly, the image is decomposed into different scales and different directions subbands by the NSCT. Then, texture features and shape features of subbands are extracted. Finally, BP neural network is used to retrieve images through using extracted features. The experimental results over car accessory images demonstrate the effectiveness of the proposed method.
Keywords
automobiles; automotive components; backpropagation; feature extraction; image retrieval; mechanical engineering computing; neural nets; transforms; BP neural network; NSCT; car accessory images; design image retrieval; nonsubsampled contourlet transform; shape feature extraction; texture feature extraction; Computed tomography; Feature extraction; Filter banks; Image retrieval; Matrix decomposition; Shape; Transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Management and Service Science (MASS), 2011 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6579-8
Type
conf
DOI
10.1109/ICMSS.2011.5998899
Filename
5998899
Link To Document