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The main drawbacks of Curvature Scale Space (CSS) matching are due to the problem of shallow and deep concavities on the shape. To solve this problem, in this paper we present a novel shape descriptor based on Extreme Curvature Scale Space (ECSS) map approach. Unlike the CSS map of shape which results from zeros crossings values of the curvature, the ECSS(More)
In this paper, we propose a new method for 2D/3D object indexing and retrieval. The principle consists of an automatic selection of optimal views by using an incremental algorithm based on pivot selection techniques for proximity searching in metric spaces. The selected views are afterward described by four well-established descriptors from the MPEG-7(More)
In order to recommend products or services to customers, many organizations are very interested in knowing the needs of their customers. For that reason, recommender systems become more required in many areas, especially in e-commerce and intelligent business. In this paper, we propose to use the similarity search in transaction databases for improving the(More)
The description of the object shape is an important characteristic of the image; several different shape descriptors are used. This paper presents a novel shape descriptor which is robust with respect to noise, scale and orientation changes of the objects. It is based on the multi scale space approach to identify shapes. The descriptor of a shape is created(More)
D-index is among the most efficient similarity search indexes, its performance dramatically depends on the choice of the ρ parameter. Although the importance of this parameter, there are no techniques or criteria proposed to choose an adequate ρ value. In this paper, we propose a criteria and a technique that ensure a good choice of ρ,(More)
In last decades, the similarity search is very required in various fields such as pattern recognition, security, and multimedia databases. Although the metric approach usefulness for speeding similarity search in complex databases, the searching cost optimization still an open problem. In this paper we propose an improvable pivot-based method which can(More)
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