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An efficient image retrieval method using adaptive weights
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DOI：10.1007/s10489-018-1174-6.png)
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Abstract
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In existing image retrieval systems using a multipoint query, the neighborhood of the various optimal query points is determined in the same way. The different nature of the various optimal query points was not taken into consideration. This approach confines the performance of the system. To overcome this confinement, in this paper, we propose an image retrieval method through adaptive weights (Aweight) which is possible to compute the various optimal query points, optimal weights and improved distance functions to improve accuracy. In addition, our method constructs clusters without re-clustering the whole feedback image set. The experiments were performed on a set of 10,800 images and the results demonstrate that the proposed method improves performance of system in terms of accuracy.
Keywords:
Content-based image retrieval (CBIR)
Multipoint query
Incremental clustering
Adaptive weights
Improved distance function
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