Point matching using asymmetric neural networks

Abstract Matching control points is an important step in many pattern recognition applications. The matching problem is formulated under translation and rotation as a 0–1 integer programming problem and an artificial neural network is proposed for approximately solving it. The solution to the 0–1 integer programming problem is obtained as the high gain limit point of the continuous network. The network is capable of handling distortion and noise and can use both interpoint distance information and feature properties associated with the points. The results obtained by the network compare favourably with that of the relaxation method of Ton and Jain (IEEE Trans. Geosci. Remote Sensing 27, 642–651 (1989)).

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