Jun Jie Foo

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Among the vast numbers of images on the web are many duplicates and near-duplicates, that is, variants derived from the same original image. Such near-duplicates appear in many web image searches and may represent infringements of copyright or indicate the presence of redundancy. While methods for identifying near-duplicates have been investigated, there(More)
Near-duplicate images introduce problems of redundancy and copyright infringement in large image collections. The problem is acute on the web, where appropriation of images without acknowledgment of source is prevalent. In this paper, we present an effective clustering approach for near-duplicate images, using a combination of techniques from invariant(More)
Duplicate and near-duplicate digital image matching is beneficial for image search in terms of collection management , digital content protection, and search efficiency. In this paper, we introduce SICO, a novel system for near-duplicate image detection during web search. It accurately detects near-duplicates in the answers returned by commercial image(More)
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