Image segmentation using statistical clustering with saddle point detection

摘要

A system and method for image segmentation using statistical clustering with saddle point detection includes representation means for representing the image data in a joint space of dimension d=r+2 that includes two special coordinates, where r=1 for gray-scale images, r=3 for color images, and r>3 for multi-spectral images; partitioning means for partitioning the data set comprising a plurality of image data points into a plurality of statistically meaningful clusters by decomposing the data set by a mean shift based data decomposition; and characterization means for characterizing the statistical significance of at least one of a plurality of clusters of data points by selecting a cluster and computing the value of a statistical measure for the saddle point lying on the border of the selected cluster and having the highest density.