Original image tracing with image relational graph for near-duplicate image elimination
by Fang Huang; Zhili Zhou; Ching-Nung Yang; Xiya Liu; Tao Wang
International Journal of Computational Science and Engineering (IJCSE), Vol. 18, No. 3, 2019

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.

Online publication date: Tue, 26-Mar-2019

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