A Multilayered Complex Network Model for Image Retrieval

In this study, an image retrieval system is proposed based on complex network model. Assuming a prior image categorization, firstly, a multilayered complex network is constructed between the images of each category according to the color, texture, and shape features. Secondly, by defining a meta-path as the way of connecting two images in the network, a set of informative meta-paths are composed to find the similar images by exploring the network. The established complex network provides an efficient way to benefit from the image correlations to enhance the similarity search of the images. On the other hand, employing diverse meta-paths with different semantics leads to measuring the image similarities based on effective image features for each category. The primary results indicate the efficiency and validity of the proposed approach.