CORN KERNEL CROWN SHAPE IDENTIFICATION USING IMAGE-PROCESSING

A machine-vision system was developed to identify different types of c rown end shapes of corn kernels. Image processing techniques were used to enhance the object and reduce noise in the acquired image. Corn ke rnels were classified as convex or dent based on their crown end shape . Dent corn kernels were further classified into smooth dent or non-sm ooth dent kernels. A one-dimensional line profile analysis was used to obtain the needed three-dimensional information. This system provided an average accuracy of approximately 87% compared to human inspection . The processing time was between 1.5 and 1.8 s/kernel.