Color image edge detection based on nonparametric density estimation

A novel computationally efficient adaptive algorithm to accomplish edge detection in multidimensional and color images is presented. It is a statistical approach, based on local, non-parametric kernel density estimation. The location of the edge discontinuity coincides with the image density function minimum and it is determined by appropriate resampling of the locally defined probability space. The operator is radially symmetric and can be easily adapted to cope with signals of any dimensionality.