This presents a system for automated classification of maize grain varieties using Artificial Neural Network. Maize Grain is the most important food crop in Myanmar. This system can classify the types of maize grain such as Butter Corn, Sweet Corn, Kalar Corn, Shan Corn. An input image of maize grain is acquired firstly by using a digital camera. The image is segmented by using threshold function and is needed to perform image processing techniques such as converting gray scale, resizing and changing to binary image. To remove the noise of an image the median filter has been used. The important features of the image are needed to be extracted according to morphological features. The seven important morphological feature extracted from images were used as input for developed ANN. This system is implemented by using MATLAB programming language.
Title = "Maize Grain Classification System using Neural Network",
Journal ="International Journal of Science and Engineering Applications (IJSEA)",
Volume = "7",
Pages ="411 - 478",
Year = "2018",
Authors ="Soe Soe Aye, Htight Htight Wai, Ei Ei Myat"}