Search (3 results, page 1 of 1)

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Abstract

The aim of this paper was to analyze users' behavior during image retrieval exercises. Results revealed that users tend to follow a set search strategy: firstly they input one or two keyword search terms one after another and view the images generated by their initial search and after they navigate their way around the web by using the 'back to home' or 'previous page' buttons. These results are consistent with existing Web research. Many of the actions recorded revealed that subjects behavior differed depending on if the task set was presented as a closed or open task. In contrast no differences were found for the time subjects took to perform a single action or their use of the AND operator.

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Abstract

XMage is introduced in this paper as a method for partial similarity searching in image databases. Region-based image retrieval is a method of retrieving partially similar images. It has been proposed as a way to accurately process queries in an image database. In region-based image retrieval, region matching is indispensable for computing the partial similarity between two images because the query processing is based upon regions instead of the entire image. A naive method of region matching is a sequential comparison between regions, which causes severe overhead and deteriorates the performance of query processing. In this paper, a new image contents representation, called Condensed eXtended Histogram (CXHistogram), is presented in conjunction with a well-defined distance function CXSim() on the CX-Histogram. The CXSim() is a new image-to-image similarity measure to compute the partial similarity between two images. It achieves the effect of comparing regions of two images by simply comparing the two images. The CXSim() reduces query space by pruning irrelevant images, and it is used as a filtering function before sequential scanning. Extensive experiments were performed on real image data to evaluate XMage. It provides a significant pruning of irrelevant images with no false dismissals. As a consequence, it achieves up to 5.9-fold speed-up in search over the R*-tree search followed by sequential scanning.

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Date

6. 1.2011 11:22:12