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Jul 8, 2015
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Abstract

Content-based image retrieval (CBIR) has been more and more important in the last decade. Visual information systems are radically different from conventional information systems. Many novel issues need to be addressed. A visual information system should be capable of providing access to the content of image. Where symbolic and numerical information are identical in content and form, images require a delicate treatment to approach their content. To search and retrieve items on the basis of their content requires a new visual way of specifying the query, new indices to order the data and new ways to establish similarity between the query and the target. In this paper, we discuss some of the key contributions in the current decade related to image retrieval and automated image annotation. We also discuss some of the key challenges involved in the benchmark datasets and adaptation of existing image retrieval techniques to build useful systems.

Keywords: Annotation, Content-based image retrieval (CBIR), Feature Extraction, Query learning, Support vector machines (SVM).

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Author Biography

Meenakshi, Ruby Panwar, Amit Kumar, Ajmer Institute of Technology, Ajmer

Asst. Professor, Department of Computer Science
How to Cite
Amit Kumar, M. R. P. (2015). Approaches and Trends in Content Based Image Retrieval System. International Journal of Emerging Trends in Science and Technology, 2(07). Retrieved from http://igmpublication.org/ijetst.in/index.php/ijetst/article/view/786

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