Estimation of Nitrogen in Rice Plant Using Image Processing and Artificial Neural Networks

This paper presents a pr ototype which identifiesthe4-panel LCC and Spad meter values equivalent of rice plants using imageprocessing techniques and artificial neural networks .  Images of rice leaveswere captured by digital camera and processed through image acquisition, color transform, image enhancement and feature extraction procedures. Suitable Features are extracted which serves as input to neural network trained to predict the LCC panel equivalent of leaf. Artificial neural network is trained using images of rice leaf with the corresponding classes using backpropogation method.