Mounira Taileb

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This paper focuses on clustering methods for content-based image retrieval CBIR. Hierarchical clustering methods are a way to investigate grouping in data, simultaneously over a variety of scales, by creating a cluster tree. Traditionally, these methods group the objects into a binary hierarchical cluster tree. Our main contribution is the proposal of a new(More)
In order to accelerate the similarity search in highdimensional database, we propose a new hierarchical indexing method. It is composed of offline and online phases. Our contribution concerns both phases. In the offline phase, after gathering the whole of the data in clusters and constructing a hierarchical index, the main originality of our contribution(More)
Content-based image retrieval (CBIR) has been one of the most important research areas in computer vision. It is a widely used method for searching images in huge databases. In this paper we present a CBIR system called NOHIS-Search. The system is based on the indexing technique NOHIS-tree. The two phases of the system are described and the performance of(More)
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