Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77388
Title: Superpixel matching based image retrieval
Authors: He, Z
Sun, X
Li, C 
Baciu, G 
Li,Y 
Keywords: Image retrieval
Key-point
Smoothing
Superpixel
Issue Date: 2017
Publisher: ACM
Source: Proceedings of the International Conference on Video and Image Processing, 2017, p. 156-160 How to cite?
Abstract: Local features of images have been widely used in image retrieval, however, the cost is so heavy. To address this issue, a superpixel-based approach for image retrieval is proposed. We first extract the image structure that preserves the main information and removes the redundant information from the image by smoothing and oversegment a smoothed image into a certain number of superpixels. We then extract the positive candidate superpixels by combining superpixels with local descriptors. Finally, we compute the similarity of two images by analyzing two sets of positive candidate superpixels. Experiments on dataset PQ7 demonstrate the performance of the proposed approach.
Description: ICVIP 2017, International Conference on Video and Image Processing, 2017, Singapore, 27–29 December, 2017
URI: http://hdl.handle.net/10397/77388
ISBN: 9781450353830
DOI: 10.1145/3177404.3177428
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

45
Citations as of Aug 14, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.