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An efficient duplicate image detection method based on Affine-SIFT feature

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4 Author(s)
Yudong Cao ; Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, China ; Honggang Zhang ; Yanyan Gao ; Jun Guo

In this paper, we present a novel scheme to tackle the task of near-duplicate image detection. Given two input images, the algorithm based on the refined similarity measure can judge rightly whether two input image are duplicate images or not. The two images are represented with local feature (i.e, Affine-SIFT) in bag of features model. The Affine-SIFT can undergo larger affine distortions than Hessian-Affine and MSER (Maximally Stable Extremal Region). The refined similarity measure exploits the spatial information between two images. The algorithm is demonstrated on some image pairs with scale change, viewpoint change, blur, noise and spatial deformation. The experimental results show that proposed algorithm is more effective than other state-of-the-art duplicate image detection algorithm.

Published in:

Broadband Network and Multimedia Technology (IC-BNMT), 2010 3rd IEEE International Conference on

Date of Conference:

26-28 Oct. 2010