- About
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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
Search results
Showing 1 to 2 of 2 (0.025 seconds)Spelling suggestions: "subject:"avståndskartor"" "subject:"avståndsdata""
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Binär matchning av bilder med hjälp av vektorer från deneuklidiska avståndstransformen / Binary matching on images using the Euclidean Distance TransformHjelm Andersson, Patrick January 2004 (has links)
<p>This thesis shows the result from investigations of methods that use distance vectors when matching pictures. The distance vectors are available in a distance map made by the Euclidean Distance Transform. The investigated methods use the two characteristic features of the distance vector when matching pictures, length and direction. The length of the vector is used to calculate a value of how good a match is and the direction of the vector is used to predict a transformation to get a better match. The results shows that the number of calculation steps that are used during a search can be reduced compared to matching methods that only uses the distance during the matching.</p>
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Binär matchning av bilder med hjälp av vektorer från deneuklidiska avståndstransformen / Binary matching on images using the Euclidean Distance TransformHjelm Andersson, Patrick January 2004 (has links)
This thesis shows the result from investigations of methods that use distance vectors when matching pictures. The distance vectors are available in a distance map made by the Euclidean Distance Transform. The investigated methods use the two characteristic features of the distance vector when matching pictures, length and direction. The length of the vector is used to calculate a value of how good a match is and the direction of the vector is used to predict a transformation to get a better match. The results shows that the number of calculation steps that are used during a search can be reduced compared to matching methods that only uses the distance during the matching.
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