An Investigation on Morphological Discrimination of Corn Kernels Based on Neural Network

With 11 selected morphological parameters and BP moment learning algorithm,a three layers feed forward neural network is formed,which can identify more than one whole or broken corn kernels positioned at random in one frame. The classification accuracy of 175 whole and 175 broken corn kernels is 93%.