Abstract
In this paper, we propose a novel method for near-duplicate image elimination by tracing the original image of each near-duplicate image cluster. To generate a similarity matrix of each cluster, both global feature and local feature are extracted to accurately evaluate the visual similarity of each image pair. According to the similarity matrix, an Image Relational Graph (IRG) is constructed. Then we adopt the graph model based link analysis algorithm PageRank to analyze the contextual relationship between images on this IRG. In this way, the original image will be correctly traced with the highest rank, while other redundant near-duplicate images in the cluster will be eliminated. To validate the performance of our proposed method, large amount of near-duplicate images mixing with distracting images are applied for experiments, and the experimental results indicate the effectiveness of our method.
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