Carl Frélicot

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Content-based copy retrieval (CBCR) aims at retrieving in a database all the modified versions or the previous versions of a given candidate object. In this paper, we present a copy retrieval scheme based on local features that can deal with very large databases both in terms of quality and speed. We first propose a new approximate similarity search(More)
Content-based copy detection (CBCD) is one of the emerging multimedia applications for which there is a need of a concerted effort from the database community and the computer vision community. Recent methods based on interest points and local fingerprints have been proposed to perform robust CBCD of images and video. They include two steps: the search of(More)
When classes strongly overlap in the feature space, or when some classes are not known in advance, the performance of a classifier heavily decreases. To overcome this problem, the reject option has been introduced. It simply consists in withdrawing the decision, and let another classifier, or an expert, take the decision whenever exclusively classifying is(More)
Color image segmentation is a fundamental task in many computer vision problems. A common approach is to use fuzzy iterative clustering algorithms that provide a partition of the pixels into a given number of clusters. However, most of these algorithms present several drawbacks: they are time consuming, and sensitive to initialization and noise. In this(More)
This paper presents a new approach to find the optimal number of clusters of a fuzzy partition. It is based on a fuzzy modeling approach which combines measures of clusters’ separation and overlap. Theses measures are based on triangular norms and a discrete Sugeno integral. Results on artificial and real data sets prove its efficiency compared to indexes(More)
In many image or video retrieval systems, the search for similar objects in the database includes a spatial access method to a multidimensional feature space. This step is generally considered as a problem independent of the features and the similarity type. The well known multidimensional nearest neighbor search has also been widely studied by the database(More)
Recent methods based on interest points and local fingerprints have been proposed to perform robust CBCD (content-based copy detection) of images and video. They include two steps: the search for similar local fingerprints in the database (DB) and a voting strategy that merges all the local results in order to perform a global decision. In most image or(More)