DocumentCode :
3708157
Title :
RST-invariant sketch retrieval based on circular description
Author :
Hanguang Zhao;Xiangwei Kong;Haiyan Fu;Yujia Zhang
Author_Institution :
School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, 116024, P.R. China
fYear :
2015
Firstpage :
4977
Lastpage :
4981
Abstract :
The explosive growth in touchscreen smartphones and tablets need simpler and intelligent image retrieval method to offer the convenience for users. Sketch based image retrieval (SBIR) which is based on a free hand sketch has recently attracted more attention, but current methods are sensitive to rotation, scaling and translation (RST). In this paper, we introduce an efficient SBIR method called RST-Invariant Circular Description (RICD). The proposed method utilizes saliency map and boundary information to detect salient contours for each image, then uses patch hashing to eliminate the deformations and redundancies of sketches. To achieve rotational invariance, we describe salient contours using circular description. The experiment results on two public datasets demonstrated that the proposed method outperforms the state-of-the-arts in both natural and product images, and handles rotation, scaling and translation transformations.
Keywords :
"Binary codes","Image retrieval","Redundancy","Indexes","Geometry","Approximation methods","Image coding"
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/ICIP.2015.7351754
Filename :
7351754
Link To Document :
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