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SKL algorithm based fabric image matching and retrieval
Author(s): Yichen Cao; Xueqin Zhang; Guojian Ma; Rongqing Sun; Deping Dong
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Paper Abstract

Intelligent computer image processing technology provides convenience and possibility for designers to carry out designs. Shape analysis can be achieved by extracting SURF feature. However, high dimension of SURF feature causes to lower matching speed. To solve this problem, this paper proposed a fast fabric image matching algorithm based on SURF K-means and LSH algorithm. By constructing the bag of visual words on K-Means algorithm, and forming feature histogram of each image, the dimension of SURF feature is reduced at the first step. Then with the help of LSH algorithm, the features are encoded and the dimension is further reduced. In addition, the indexes of each image and each class of image are created, and the number of matching images is decreased by LSH hash bucket. Experiments on fabric image database show that this algorithm can speed up the matching and retrieval process, the result can satisfy the requirement of dress designers with accuracy and speed.

Paper Details

Date Published: 21 July 2017
PDF: 5 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104201F (21 July 2017); doi: 10.1117/12.2285415
Show Author Affiliations
Yichen Cao, East China Univ. of Science and Technology (China)
Xueqin Zhang, East China Univ. of Science and Technology (China)
Guojian Ma, East China Univ. of Science and Technology (China)
Rongqing Sun, East China Univ. of Science and Technology (China)
Deping Dong, East China Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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