A Relative Study to Compare Image Annotation using Ontology for Semantic Web
Technology plays a vital role in inventions such as photography and television, and facilitates the capturing and communication of image data. The progression of multimedia technology solicits the users thrust in various fields such as medicine, journalism, advertising, design, education and entertainment. The challenge of finding a desired picture in a wide and diverse set was one of the key issues they highlighted. Users in many professional fields are exploiting the opportunities offered, the ability to access and manipulate remotely-stored images using exciting methods. However, the process of locating a desired image in a large and varied collection can be a source of considerable frustration. The problems of image retrieval are becoming widely recognized, and the search for solutions is the active area for research and development. Content Based Image Retrieval searches the given image from set of images by using efficient image descriptors. Relevance feedback was incorporated into CBIR to make it more beneficial. However, for large and high dimensional image databases, it is obvious that the current retrieval techniques are unable to produce proper milestones for image retrieval. The main focus of this paper is to analyze the various image retrieval systems and to optimize the searching technique. In the proposed technique the images are categorized based on concepts in various domains. This paper deals with comprehensive survey of the technical achievements in the research area of image retrieval, especially content-based image retrieval, semantic image retrieval and ontology techniques which is playing a active role in current scenario.