Counting Ear Rows in Maize Using Image Process Method

Ear Rows is an important agricultural character in Maize (Zea mays L.). In order to exam feasibility of ear rows counting method by machine vision, a new method was raised. This method is based on edge marker and discrete curvature. 78 digital images of 4 maize cultivars were scanned from 2 sides if maize fragment face. Based on this, we find that that the number is mostly 12-18, and the detecting absolute error is 0.103 and relative error rate is 0.66%. The accuracy rate is above 90%. Machine vision wins the advantages of low cost and high speed over manual or biochemical detecting methods, and is feasible to be applied to identification of numerous maize cultivars.