Applying Segmented Images by Louvain Method into Content-Based Image Retrieval

Overview & Synopsis

The amount of multimedia data has increased on personal computers and the Internet requires the essential to finding a particular image or a collection of images have enhanced of demands. It urges researchers to propose new sophisticated methods to retrieve the information one desires. In the case of, the legacy approach cannot grow up with the rapid rate of available data anymore. Therefore, content-based image retrieval (CBIR) has attracted many researchers to various fields. Content-based image retrieval models attempt to effort to automate data analysis and indexing. In this paper, we propose a content-based image retrieval system for real images. This method is using segmented images by the Louvain method [26] to create features in order to apply to the CBIR system based on the Bag-of-Visual-Words (BoVW) model. In order to evaluate the proposed method, we selected the Corel dataset which is composed of 10 classes [14] total of 1000 images in the dataset for the experiment. The experimental results are shown using qualitative and quantitative evaluations.