Psri Target Recognition In Range Imagery Using Neural Networks

S. E. Troxel; S. K. Rogers; M. Kabrisky; J. P. Mills

doi:10.1117/12.976605

22 August 1988 Psri Target Recognition In Range Imagery Using Neural Networks

S. E. Troxel, S. K. Rogers, M. Kabrisky, J. P. Mills

Proceedings Volume 0938, Digital and Optical Shape Representation and Pattern Recognition; (1988) https://doi.org/10.1117/12.976605
Event: 1988 Technical Symposium on Optics, Electro-Optics, and Sensors, 1988, Orlando, FL, United States

Abstract

A method for classifying objects invariant to position, rotation, or scale is presented. Objects to be classified were multifunction laser radar data of tanks and trucks at various aspect angles. A segmented doppler image was used to mask the range image into candidate targets. Each target is then compared to stored templates representing the different classes. The template and the image were transformed into the magnitude of the Fourier transform with log radial and angle axis, lF (Ln r , 0)1, feature space. The classification is accomplished using the shape of the correlation peak of the IF (Ln r , 0)1 planes of an image and a template. A neural network was used to perform the classification with a classification accuracy near 100%. The neural network used in this study was a multilayer perception using a back propagation algorithm.

Citation Download Citation

S. E. Troxel, S. K. Rogers, M. Kabrisky, and J. P. Mills "Psri Target Recognition In Range Imagery Using Neural Networks", Proc. SPIE 0938, Digital and Optical Shape Representation and Pattern Recognition, (22 August 1988); https://doi.org/10.1117/12.976605

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