Content-Based Image Retrieval Using Binary Signatures

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  • Technical report TR00-18. Significant research has focused on determining efficient methodologies for retrieving images in large image databases. In this paper, we propose two variations of a new image abstraction technique based on signature bit-strings and an appropriate similarity metric. The technique provides a compact representation of an image based on its color content and yields better retrieval effectiveness than classical techniques based on the images' global color histograms (GCHs) and color coherence vectors (CCVs). The technique is also well-suited for use in a grid-based approach, where information about the spatial locality of colors can be taken into account. Performance evaluation of image retrieval on a heterogeneous database of 20,000 images demonstrated that the proposed technique outperforms the use of GCHs by up to 50%, and the use of CCVs by up to 20% in terms of retrieval effectiveness -- this relative advantage was also observed when using classical Precision vs Recall curves. Perhaps more importantly is the fact that our approach saves 75% of storage space when compared to using GCHs and 85.5% when using CCVs. That makes it possible to store and search an image database of reasonable size, e.g., hundreds of thousands of images, using a few megabytes of main memory, without the aid of (complex) disk-based access structures. | TRID-ID TR00-18

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    Attribution 3.0 International