System and method for image and video segmentation by anisotropic kernel mean shift

A system for segmenting image data, comprising:

• defining an anisotropic kernel of influence for each pixel in an image, wherein said kernel defines a measure of intuitive distance between pixels, where distance encompasses both spatial/lattice and range/color distance;
• and
• assigning to each pixel a mean shift point initialized to coincide with said pixel;
• iteratively moving each mean shift point upwards along the gradient of the kernel density function defined by the sum of all the kernels until they reach a stationary point;
• and
• considering pixels that are associated with the set of mean shift points that migrate to the approximately same stationary point to be members of a single segment.

A computer-readable storage medium encoded with computer executable instructions for segmenting image data, said computer executable instructions comprising:

• inputting image data;
• and
• segmenting said image data using a mean shift segmentation technique employing generally elliptical kernels wherein the computer-executable instruction for segmenting said image data comprises sub-instructions for:
• initializing kernel data;
• for each feature point, determining a kernel being a product of kernels with at least one of these kernels being elliptical;
• associating a mean shift point with every feature point and initializing said mean shift point to coincide with that feature point;
• updating mean shift points by an iterative anisotropic mean shift update;
• and
• merging vectors associated with feature points that are approximately the same to produce homogeneous color regions.