A new similarity measure using hausdorff distance map

Image dissimilarity measure is a hot topic. The measure process is generally composed of an information mining in each image which results in an image signature and then a signature comparison to take the decision about the image similarity. In the scope of binary images, we propose in this paper to replace the information mining by a new straight image comparison which does not require a priori knowledge. The second stage is then replaced by a decision process based on the image comparison. The new comparison process is structured as follows: a morphological multiresolution analysis is applied to the two images. Secondly a distance map is constructed at each scale by the computation of the Hausdorff distance restricted through a slidingwindow. A signature is then extracted from the distance map and is used to take the decision. As an application, the algorithm has been successfully tested on an ancient illustration database.

• Type: Conference
• Year: 2004
• Where: ICIP
• Authors: Etienne Baudrier, Frédéric Nicolier, Gilles Millon, Su Ruan
• Keywords: ICIP 2004, Image Dissimilarity Measure, Image Processing, Image Signature, Image Similarity, Signature Comparison, Straight Image Comparison