Share Email Print

Proceedings Paper

Natural texture retrieval based on perceptual similarity measurement
Author(s): Ying Gao; Junyu Dong; Jianwen Lou; Lin Qi; Jun Liu
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

A typical texture retrieval system performs feature comparison and might not be able to make human-like judgments of image similarity. Meanwhile, it is commonly known that perceptual texture similarity is difficult to be described by traditional image features. In this paper, we propose a new texture retrieval scheme based on texture perceptual similarity. The key of the proposed scheme is that prediction of perceptual similarity is performed by learning a non-linear mapping from image features space to perceptual texture space by using Random Forest. We test the method on natural texture dataset and apply it on a new wallpapers dataset. Experimental results demonstrate that the proposed texture retrieval scheme with perceptual similarity improves the retrieval performance over traditional image features.

Paper Details

Date Published: 10 April 2018
PDF: 7 pages
Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106154W (10 April 2018); doi: 10.1117/12.2304752
Show Author Affiliations
Ying Gao, Ocean Univ. of China (China)
Junyu Dong, Ocean Univ. of China (China)
Jianwen Lou, Univ. of Portsmouth (United Kingdom)
Lin Qi, Ocean Univ. of China (China)
Jun Liu, Qingdao Agricultural Univ. (China)

Published in SPIE Proceedings Vol. 10615:
Ninth International Conference on Graphic and Image Processing (ICGIP 2017)
Hui Yu; Junyu Dong, Editor(s)

© SPIE. Terms of Use
Back to Top