  This paper presents a genetic stereo matching algorithm with fuzzy evaluation
function. The proposed algorithm presents a new encoding scheme in which a
chromosome is represented by a disparity matrix. Evolution is controlled by a
fuzzy fitness function able to deal with noise and uncertain camera
measurements, and uses classical evolutionary operators. The result of the
algorithm is accurate dense disparity maps obtained in a reasonable
computational time suitable for real-time applications as shown in experimental
results.
