%0 Journal Article
%T Weed recognition method based on color and morphological features in wheat field<br>综合颜色和形态特征的小麦田杂草识别方法
%A ZHU Wei-xing
%A JIN Fei-jian
%A TAN Rong-rong
%A <br>朱伟兴
%A 金飞剑
%A 谈蓉蓉
%J 计算机应用
%D 2007
%I 
%X The technology of weed recognition based on machine vision becomes a hot issue of precision agriculture. Concerning the severe occluding of leaves of weed and wheat, a weed identification method was proposed with color and morphological features. Color feature was utilized to distinguish plants and background: a* was taken as characteristic variant in L*a*b* color space, and the improved method of maximum classes square error was taken as the criterion; Color feature was utilized to distinguish wheat and weed: hierarchical approach was used to color image segmentation in HSI color space; Morphological feature was utilized to obtain weed: using morphological opening and closing filter, and AND operation algorithm. The proposed methods together with a chemical weeding system were simulated and the efficiency of the overall system was evaluated theoretically. The experimental results on a series of weed images show that the correct identification rate exceeds 92.6%, and the herbicide reduction rate exceeds 72.4%.
%K weed recognition
%K machine vision
%K morphological
%K homogeneity
%K AND operation<br>杂草识别
%K 机器视觉
%K 形态学
%K 同质性
%K 与运算
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=24C85957D856D56283602DAF8DDAD890&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=708DD6B15D2464E8&sid=F7625C90E0BC702B&eid=29EF3FA9A2182B88&journal_id=1001-9081&journal_name=计算机应用&referenced_num=1&reference_num=10