Kouahla ZİNEDDİNE, Ferrag MOHAMED AMİNE, Anjum ADEEL

Indexing Multimedia Data with an Extension of Binary Tree -- Image Search by Content --

Searching for similar images in a data collection, based on a query image, is a fundamental problem for many applications that use large amounts of complex data. Image research by content and on a large scale is a current challenge for large image database research and management. Various information can be extracted such as colour, shape and texture, etc. A characteristic represents only a part of the image property, which makes it necessary to combine all this information to improve the efficiency of these systems. This paper aims to propose a new indexing structure that allows to organize as much information as possible about the images in a binary tree in order to improve the search time, and to propose an algorithm for index construction and a search algorithm for kNN type queries. The concept of containers at the sheet level was used to improve the complexity of algorithms. Experiments on real data sets were conducted to determine its performance.

Keywords:

Metric Space, Tree Large Scale, Image, Intrinsic Dimension,

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