Neural-network-based object recognition scheme directly from the boundary information
Kootala P. Venugopal, Anil D. Mandalia, Salahalddin T. Abusalah · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
We describe a neural network based recognition scheme for 2-D objects directly from the boundary information. The encoded boundary of the object is directly fed as input to the neural network cutting short the feature extraction stage and hence making the scheme computationally simpler. Also, the described scheme is invariant to translation, rotation, and scale changes to the objects. Using isolated hand-written digits, we show that the proposed scheme provides recognition accuracy of up to 87%. The error backpropagation method is used as the learning algorithm for the neural network.