@inproceedings{7404c16951c04260ac8b0b6c99f88dde,
title = "Natural texture retrieval based on perceptual similarity measurement",
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.",
author = "Ying Gao and Junyu Dong and Jianwen Lou and Lin Qi and Jun Liu",
year = "2018",
month = apr,
day = "10",
doi = "10.1117/12.2304752",
language = "English",
isbn = "9781510617414",
series = "Proceedings of SPIE",
publisher = "SPIE Press",
editor = "Hui Yu and Junyu Dong",
booktitle = "Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017)",
note = "Ninth International Conference on Graphic and Image Processing ; Conference date: 14-10-2017 Through 16-10-2017",
}