A review of ROI image retrieval techniques

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Abstract

Content based image retrieval involves extraction of global and region features of images for improving their retrieval performance in large image databases. Region based feature have shown to be more effective than global features as they are capable of reflecting users specific interest with greater accuracy. However success of region based methods largely depends on the segmentation technique used to automatically specify the region of interest (ROI) in the query. Apart from this user can also specify ROI’s in an image. The ROI image retrieval involves the task of formulation of region based query, feature extraction, indexing and retrieval of images containing similar region as specified in the query. In this paper state-of-the-art techniques for ROI image retrieval are discussed. Comparative study of each of these techniques together with pros and cons of each technique are listed. The paper is concluded with our views on challenges faced by researchers and further scope of research in the area. The major goal of the paper is to provide a comprehensive reference source for the researchers involved in image retrieval based on ROI.

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Shrivastava, N., & Tyagi, V. (2015). A review of ROI image retrieval techniques. In Advances in Intelligent Systems and Computing (Vol. 328, pp. 509–520). Springer Verlag. https://doi.org/10.1007/978-3-319-12012-6_56

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