International Journal of applied mathematics and computer science

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Paper details

Number 2 - June 2016
Volume 26 - 2016

Content-based image retrieval using a signature graph and a self-organizing map

Thanh The Van, Thanh Manh Le

Abstract
In order to effectively retrieve a large database of images, a method of creating an image retrieval system CBIR (content-based image retrieval) is applied based on a binary index which aims to describe features of an image object of interest. This index is called the binary signature and builds input data for the problem of matching similar images. To extract the object of interest, we propose an image segmentation method on the basis of low-level visual features including the color and texture of the image. These features are extracted at each block of the image by the discrete wavelet frame transform and the appropriate color space. On the basis of a segmented image, we create a binary signature to describe the location, color and shape of the objects of interest. In order to match similar images, we provide a similarity measure between the images based on binary signatures. Then, we present a CBIR model which combines a signature graph and a self-organizing map to cluster and store similar images. To illustrate the proposed method, experiments on image databases are reported, including COREL, Wang and MSRDI.

Keywords
binary signature, similarity measure, signature graph, image retrieval

DOI
10.1515/amcs-2016-0030