南京理工大学学报（自然科学版）2016，Vol.40Issue(6)：661-665,5.DOI:10.14177/j.cnki.32-1397n.2016.40.06.004
基于机器视觉的玉米雄穗识别算法
Corn tassel recognition algorithm based on machine vision
摘要
Abstract
A corn tassel segmentation algorithm is proposed for corn field large area images to determine corn tasseling stage automatically. Firstly,a red green blue(RGB)image is converted to the YCbCr space,Cb and Cr component images are enhanced respectively;then a Fisher classifier is trained to classify the Cb and Cr value of each pixel and corn tassels are segmented preliminary;next,a new color index excess blue index( ExB) is used to gray the RGB image,and the gray image is clustered by an improved Kmeans;lastly,the Fisher classification results and clustering results are combined to determine final corn tassel pixels. Experimental results show that this algorithm can identify corn tassels effectively,fault rate and recall rate of a normal environment are 0. 177% and 0. 831% respectively,fault rate and recall rate of a drought environment are 0. 141% and 0. 811%respectively,this algorithm is robust for maize growth environments.关键词
机器视觉/玉米/雄穗/识别/抽雄期/错分率/查全率Key words
machine vision/corn/tassels/recognition/corn tasseling stage/fault rate/recall rate分类
信息技术与安全科学引用本文复制引用
茅正冲,刘永娟..基于机器视觉的玉米雄穗识别算法[J].南京理工大学学报（自然科学版）,2016,40(6):661-665,5.基金项目
国家自然科学基金(60973095) （60973095）
江苏省自然科学基金(BK20131107) （BK20131107）
