Complementary semantic model for content-based image retrieval

Multimedia technology is known as the single repository source for information retrieval that includes images, audio and video. Nowadays, it is growing with tremendous amount in the field of communication technology. Traditional text based retrieval techniques of information retrieval are inefficient at searching user´s intended information from the large multimedia database. To address this problem, content based image retrieval techniques are applied for information retrieval. Content-based image retrieval has been hot topic from past two decades by many researchers´ community. This topic covers many fields such as image processing, artificial intelligence, pattern recognition, and data mining and beside other related area. In this paper image retrieval techniques on the basis of color, texture and shape are explained, studies and compared. While relevance feedback technique, system accuracy, efficiency have also been discussed. Emphasize on the concept of `semantic-based image retrieval techniques´ have been proposed in this paper, which is better technique to overcome the problem of `semantic gap´ in the context of image retrieval.