These codes of general interest are made available "as it is".
Please acknowledge their use by referring to this webpage.

Edge Detection and Image SegmentatiON (EDISON) System

C++ code, can be used through a graphical interface or command line.
The system is described in Synergism in low level vision.
For comments, please contact Bogdan Georgescu or Chris M. Christoudias.

The EDISON system contains the image segmentation/edge preserving filtering algorithm described in the paper Mean shift: A robust approach toward feature space analysis and the edge detection algorithm described in the paper Edge detection with embedded confidence.

Adaptive mean shift based clustering

C++ code implementing an (approximate) mean shift procedure with variable bandwith (in high dimensions). The algorithm is described in Mean shift based clustering in high dimensions: A texture classification example.
For comments, please contact Bogdan Georgescu or Ilan Shimshoni.

Color distribution and optical flow based point matcher

C++ code to find point correspondences by matching color distributions computed with spatially oriented kernels and optical flow registration. The theory is described in Point Matching Under Large Image Deformations and Illumination Changes.
For comments, please contact Bogdan Georgescu.

Heteroscedastic Regression

C++ code implementing the estimation of errors-in-variables models under point dependent noise. It includes examples for linear, ellipse, fundamental matrix and trifocal tensor estimation. The theory is described in A general method for errors-in-variables problems in computer vision.
For comments, please contact Bogdan Georgescu.