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ICPR
2006
IEEE

A fast binary-image comparison method with local-dissimilarity quantification

12 years 11 months ago
A fast binary-image comparison method with local-dissimilarity quantification
Image similarity measure is widely used in image processing. For binary images that are not composed of a single shape, a local comparison is interesting but the features are usely poor (color) or difficult to extract (texture, forms). We present a new binary image comparison method that uses a windowed Hausdorff distance in a pixel-adaptive way. It enables to quantify the local dissimilarities and to give their spatial distribution which greatly improve the dissimilarity information. Combined with a Support Vector Machine classifier, this method is successfully tested on an medieval-impression database. Keywords Image comparison, binary images, Hausdorff distance, local dissimilarity measure, classification, SVM.
Etienne Baudrier, Frédéric Nicolier,
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2006
Where ICPR
Authors Etienne Baudrier, Frédéric Nicolier, Gilles Millon, Su Ruan
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