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Shape based local affine invariant texture characteristics for fabric image retrieval

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Abstract

The rapid growth of fabric images needs fast retrieval for related applications, such as fashion design. The goal of fabric image retrieval is to retrieve and rank relevant fabrics from a large scale fabric database to visually assist users’ online shopping process in e-commerce. Most of existing solutions to this issue are not invariant with respect to 2D similarity or affine transformations, much less to 3D transformations of textured surface. In this paper, we propose a new search method with a shape based local affine invariant texture characteristics. By employing topographic map to represent fabric images, which is a complete, multi-scale and contrast invariant representation, the proposed method first obtains a tree of shapes from the topographic map. Then, a group of statistics is applied on these shapes to acquire a set of features that are invariant to 3D transformations. We finally represent these features combing relations between shapes, and based on the representation the similarity of pairs of fabric images can be estimated. To evaluate the performance of our algorithm, we conducted a series of experiments on a real-world fabric image dataset, and compared the proposed method with other previous ones. Experimental results demonstrate that the time of the proposed method spending in searching is less than 1 second, and meanwhile a higher PR score than others is obtained.

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Acknowledgements

This research is jointly supported by the National Natural Science Foundation of China (U1504608, 61672471, 61762050, 61602222), and the Jiangxi Natural Science Foundation (No.20161BAB212043).

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Correspondence to Jianwei Zhang.

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Li, Y., Zhang, J., Chen, M. et al. Shape based local affine invariant texture characteristics for fabric image retrieval. Multimed Tools Appl 78, 15433–15453 (2019). https://doi.org/10.1007/s11042-018-6936-y

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