This work addresses the problem of segmenting an image into regions. We first define a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an efficient segmentation algorithm based on this predicate. \\
We apply the algorithm to image segmentation using two different dissimilarity between pixels : the Euclidean distance and a new empirical distribution-based dissimilarity. We illustrate the results so that we can underline the contribution of this new dissimilarity to image segmentation.
|Date of Award||2007|
|Supervisor||Jean Paul Rasson (Supervisor), Andre Hardy (Jury), Marcel Remon (Jury) & François Roland (Jury)|