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Our region-based image retrieval system applies the Earth Mover's Distance in the design of the similarity measure for image ranking and matching.
This paper proposes a new measure for image quality assessment (IQA), which supplies more flexibility than previous methods in using the pixel displacement in the assessment.
We use entropy as a measure for image quality.
This kernel was successfully used as a similarity measure for image retrieval and recognition tasks [38, 39].
The height of the peak gives a good similarity measure for image matching, and the location of the peak shows the translational displacement between the images.
Finally, it is demonstrated how optimisation-based colour quantisation can be employed in conjunction with a more appropriate measure for image quality.
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This paper describes a similarity measure for images which can be used in image-based topological localization and topological SLAM problems by autonomous robots with low computational resources.
Although the Win Ratio may be adequate for some research designs, the Elo Score provides a more discriminating measure for images that elicit strong responses.
> 20,000 particles were morphologically measured for image analysis.
"Ordinal Measures for Image Correspondence," Vol. 20, No. 4, pp. 415-423, Apr.
Factors to consider when designing quality assessment measures for image segmentation are discussed.
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