Neural-network-based object recognition scheme directly from the boundary information

Kootala P. Venugopal; Anil D. Mandalia; S. Abusalah

doi:10.1117/12.138219

9 July 1992 Neural-network-based object recognition scheme directly from the boundary information

Kootala P. Venugopal, Anil D. Mandalia, S. Abusalah

Proceedings Volume 1699, Signal Processing, Sensor Fusion, and Target Recognition; (1992) https://doi.org/10.1117/12.138219
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

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.

Citation Download Citation

Kootala P. Venugopal, Anil D. Mandalia, and S. Abusalah "Neural-network-based object recognition scheme directly from the boundary information", Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); https://doi.org/10.1117/12.138219

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