SIZE GRADING OF CORN KERNELS WITH MACHINE VISION

Bin Ni, Marvin R Paulsen, John F. Reid

Applied Engineering in Agriculture · 1998 · 21 citations · 0 references

Concepts

Abstract

An electronic corn kernel size grading system was developed using machine vision. Measurements of kernellength, width, and projected area were obtained independent of kernel orientation. The performance of the size-gradingalgorithm was compared to the results of mechanical sieving using a precision round-hole seed sizer. Average accuracyfrom 73.8% to 90.3% was achieved on seed corn samples that were pre-sized using precision graders.