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We present a novel approach to shape similarity estimation based on distance transformation and ordinal correlation. The proposed method operates in three steps: object alignment, contour to multilevel image transformation, and similarity evaluation. This approach is suitable for use in shape classification, content-based image retrieval, and performance(More)
Recall of spatial location was studied with 5, 8, 12--13, and 17--18 year old subjects. Pictures of objects were shown one at a time in one of the four quadrants of a projection screen which was either blank (NF) or divided by a cross into four quadrants (F). The presence of the frame (F) did not affect item recall, but facilitated location recall more, the(More)
The alignment of the object is based on universal and optimal axes introduced in [1] and [2], respectively. In our version of the algorithm we are using, µ=2l, for the axes. It has been chosen arbitrarily. Usually, parameter µ can be a constant or a function µ(l) of l. Any non-negative function of domain N={natural numbers} can be used as µ, which is the(More)
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