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2020 | OriginalPaper | Buchkapitel

Single Color Sketch-Based Image Retrieval in HSV Color Space

verfasst von : Yu Xia, Shuangbu Wang, Yanran Li, Lihua You, Xiaosong Yang, Jian Jun Zhang

Erschienen in: Transactions on Computational Science XXXVII

Verlag: Springer Berlin Heidelberg

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Abstract

Sketch-based image retrieval is a fundamental computer vision problem. Instead of using hand-designed features to represent sketches and images, recent researches apply deep learning approaches combined with fine-grained matching to retrieve images with fine-grained details. Although these researches allow user to use hand-free sketches drawn for retrieving similar objects, the color matching is ignored which induces a low retrieval precision. To address this problem, we propose a single color sketch-based image retrieval (SCSBIR) approach using HSV color feature considering both shape matching and color matching in this paper. The SCSBIR problem is investigated using deep learning networks, in which deep features are used to represent color sketches and images. A novel ranking method considering both shape matching and color matching is also proposed. In addition, we build a SCSBIR dataset with color sketches and images, and train and test our method by using this dataset. The test results show that our method has a better retrieval performance. The research in this paper can not only promote its application in the commercial field, but also provide reference for the future research in this field.

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Titel: Single Color Sketch-Based Image Retrieval in HSV Color Space
verfasst von: Yu Xia
Shuangbu Wang
Yanran Li
Lihua You
Xiaosong Yang
Jian Jun Zhang
Verlag: Springer Berlin Heidelberg
Buch: Transactions on Computational Science XXXVII
Print ISBN: 978-3-662-61982-7

Electronic ISBN: 978-3-662-61983-4

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-662-61983-4_5

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