title: Interactive image segmentation via adaptive weighted distances.
abstract: An interactive algorithm for soft segmentation of natural images is presented in this paper. The user first roughly scribbles different regions of interest, and from them, the whole image is automatically segmented. This soft segmentation is obtained via fast, linear complexity computation of weighted distances to the user-provided scribbles. The adaptive weights are obtained from a series of Gabor filters, and are automatically computed according to the ability of each single filter to discriminate between the selected regions of interest. We present the underlying framework and examples showing the capability of the algorithm to segment diverse images.
authors.affiliation: Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA. alexis.protiere@polytechnique.edu
authors.forename: Alexis
authors.initials: A
authors.lastname: Protiere
authors.forename: Guillermo
authors.initials: G
authors.lastname: Sapiro
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity