Natural texture retrieval based on perceptual similarity measurement

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

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    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.
    Original languageEnglish
    Title of host publicationProceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017)
    EditorsHui Yu, Junyu Dong
    PublisherSPIE Press
    ISBN (Electronic)9781510617421
    ISBN (Print)9781510617414
    DOIs
    Publication statusPublished - 10 Apr 2018
    EventNinth International Conference on Graphic and Image Processing - Qingdao, China
    Duration: 14 Oct 201716 Oct 2017

    Publication series

    NameProceedings of SPIE
    PublisherSPIE
    Volume10615
    ISSN (Print)0277-786X

    Conference

    ConferenceNinth International Conference on Graphic and Image Processing
    Country/TerritoryChina
    CityQingdao
    Period14/10/1716/10/17

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