in this paper, we used a shape matching algorithm to recognize farsi digits. for each sampled point on the contour of a shape, we obtain a descriptor showing the distribution of the other points of the contour, with respect to this point. based on these descriptors, we find the corresponding points of the two contours and take the sum of their distances as a dissimilarity measure between two sh...

A dissimilarity measure for shapes described by their contour, the Cyclic Dynamic Time Warping (CDTW) dissimilarity, is introduced. The dissimilarity measure is based on Dynamic Time Warping of cyclic strings, i.e., strings with no definite starting/ending points. The Cyclic Edit Distance algorithm by Maes cannot be directly extended to compute the CDTW dissimilarity, as we show in the paper. W...

in this paper, the performance of 11 different distances for image retrieval and classification, based on color, shape and texture, is evaluated. the precision-recall measure and the correct classification rate of the k-nn classifier are used to evaluate retrieval and classification performances, respectively. the experimental results for a database of 1000 images from 10 different semantic gro...

Similarity: measure of how close to each other two instances are. The “closer” the instances are to each other, the larger is the similarity value. Dissimilarity: measure of how different two instances are. Dissimilarity is large when instances are very different and is small when they are close. Proximity: refers to either similarity or dissimilarity Distance metric: a measure of dissimilarity...