Title: Original image tracing with image relational graph for near-duplicate image elimination

Authors: Fang Huang; Zhili Zhou; Ching-Nung Yang; Xiya Liu; Tao Wang

Addresses: Jiangsu Engineering Centre of Network Monitoring and School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China ' Jiangsu Engineering Centre of Network Monitoring and School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China; Department of Electrical and Computer Engineering, University of Windsor, Windsor, Ontario, Canada ' Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien City 974, Taiwan ' Jiangsu Engineering Centre of Network Monitoring and School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China ' Jiangsu Engineering Centre of Network Monitoring and School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China

Abstract: This paper proposes a novel method for near-duplicate image elimination, by tracing the original image of each near-duplicate image cluster. For this purpose, image clustering based on the combination of global feature and local feature is firstly achieved in a coarse-to-fine way. To accurately eliminate redundant images of each cluster, image relational graph is constructed to reflect the contextual relationship between images, and PageRank algorithm is adopted to analyse this contextual relationship. Then the original image will be correctly traced with the highest rank, while other redundant near-duplicate images in the cluster will be eliminated. Experiments show that our method achieves better performance in both image clustering and redundancy elimination, compared with the state-of-the-art methods.

Keywords: near-duplicate image clustering; near-duplicate image elimination; image retrieval; image search; near-duplicate image retrieval; partial-duplicate image retrieval; image copy detection; local feature; contextual relationship.

DOI: 10.1504/IJCSE.2019.098540

International Journal of Computational Science and Engineering, 2019 Vol.18 No.3, pp.294 - 304

Received: 28 Sep 2016
Accepted: 06 Feb 2017
Published online: 26 Mar 2019 *

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