Patent ID: 7039239
Filing Date: 2006-05-02
Classification: G06K

Abstract:
1. A method for classification of image regions by probabilistic merging of a class probability map and a cluster probability map, said method comprising the steps of: a) extracting one or more features from an input image composed of image pixels; b) performing unsupervised learning based on the extracted features to obtain a cluster probability map of the image pixels; c) performing supervised learning based on the extracted features to obtain a class probability map of the image pixels; and d) combining the cluster probability map from unsupervised learning and the class probability map from supervised learning to generate a modified class probability map to determine the semantic class of the image regions; wherein the unsupervised learning in step b) comprises the steps of: determining number of clusters in the input image; estimating parameters of a probabilistic model describing the clusters; and assigning each image pixel to one of the clusters according to the probabilistic model.