Title :
Information fusion in computer vision using the fuzzy integral
Author :
Tahani, Hossein ; Keller, James M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Missouri Univ., Columbia, MO, USA
Abstract :
A method of evidence fusion, based on the fuzzy integral, is developed. This technique nonlinearly combines objective evidence, in the form of a fuzzy membership function, with subjective evaluation of the worth of the sources with respect to the decision. Various new theoretical properties of this technique are developed, and its applicability to information fusion in computer vision is demonstrated through simulation and with object recognition data from forward-looking infrared imagery
Keywords :
computer vision; computerised pattern recognition; computerised picture processing; fuzzy set theory; computer vision; evidence fusion; forward-looking infrared imagery; fuzzy integral; fuzzy membership function; information fusion; object recognition data; Automatic control; Bayesian methods; Computer vision; Curve fitting; End effectors; Fuzzy systems; Interpolation; Robot kinematics; Robotics and automation; Spline;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
