Pasi Reijonen

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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)
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)
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)
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