Natural texture retrieval based on perceptual similarity measurement

Ying Gao; Junyu Dong; Jianwen Lou; Lin Qi; Jun Liu

doi:10.1117/12.2304752

10 April 2018 Natural texture retrieval based on perceptual similarity measurement

Ying Gao, Junyu Dong, Jianwen Lou, Lin Qi, Jun Liu

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106154W (2018) https://doi.org/10.1117/12.2304752
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

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.

Citation Download Citation

Ying Gao, Junyu Dong, Jianwen Lou, Lin Qi, and Jun Liu "Natural texture retrieval based on perceptual similarity measurement", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106154W (10 April 2018); https://doi.org/10.1117/12.2304752

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