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A Novel Approach for Content-Based Image Indexing and Retrieval System using Global and Region Features


Suresh Pabboju, A.Venu Gopal Reddy


Vol. 9  No. 2  pp. 119-130


Recently, digital content has become a significant and inevitable asset for any enterprise and the need for visual content management is on the rise as well. There has been an increase in attention towards the automated management and retrieval of digital images owing to the drastic development in the number and size of image databases. A significant and increasingly popular approach that aids in the retrieval of image data from a huge collection is called Content-based image retrieval (CBIR). Content-based image retrieval has attracted voluminous research in the last decade paving way for development of numerous techniques and systems besides creating interest on fields that support these systems. CBIR indexes the images based on the features obtained from visual content so as to facilitate speedy retrieval. In this paper, we have presented an elegant and effective system for content-based image indexing and retrieval. The system exploits the global and regional features of the images for indexing and fractional distance measure as similarity measure for retrieval. The images are quantized before extracting the global features. We have also presented a novel approach for image segmentation to extract the region features effectively. R*-Tree data structure is used in indexing the region features. The experimental results show that the proposed system can improve the retrieval accuracy as well as reduce the time for retrieval.


Content Based Image Indexing (CBII), Content-Based Image Retrieval (CBIR), Global Features, Region Features, Lab Color space, Edge detection, Segmentation, R*-Tree Structure, Fractional Distance Measure