Framework for image retrieval using protégé

Abstract

Image Retrieval (IR) is the elementary requirement in present scenario as huge amount of images of different types are being added in database from different sources. For retrieval of the particular image, different kinds of processing are required to extract the relevant features from them. The Text Based Image Retrieval (TBIR) adopts the method of appending descriptions and keywords to the images which act as an alternative for the annotation words in providing exact or similar results. In order to overcome the limitations of traditional methods, the trending research study named Content Based Image Retrieval (CBIR) can be adopted. The ideology of CBIR relies on retrieving similar images from the training set using the image features like shape, texture and color. A hybrid approach named semantic based image Retrieval (SBIR) is proposed for the efficient retrieval of images by including the semantic descriptions from TBIR and the low level features of CBIR to reduce the semantic gap. In this paper, the tool named protégé is elaborated to handle the accurate results basing on RDF and OWL.