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作 者:田有文[1] 郑鹏辉[1] 许童羽[1] 邓寒冰[1] 王泷[1]
机构地区:[1]沈阳农业大学信息与电气工程学院,辽宁沈阳110866
出 处:《计算机工程与设计》2016年第5期1411-1416,共6页Computer Engineering and Design
基 金:国家科技支撑计划基金项目(2013BAD20B08);辽宁省科技特派基金项目(2013301004-7);辽宁省"博士后集聚工程"基金项目(2011921012)
摘 要:针对以往繁琐、有损的叶部病害程度检测问题,研发基于Android平台的黄瓜叶部病害严重程度实时无损检测系统。采用迭代式阈值法分割叶片区域和背景区域;采用模糊C均值聚类算法提取病斑区域,计算病斑区域像素点个数与整个叶片区域像素点个数的比值k;根据相关病害分级标准,判断黄瓜叶部病害的严重程度,利用SQLite数据库技术,动态添加其它黄瓜病害分级标准和防控措施信息;将检测结果及防控措施显示在手机屏幕上。实验结果表明,该系统能够在田间对黄瓜叶部病害进行实时无损检测,准确快速地对其病害程度进行判定。Aiming at the problems of leaf disease severity detecting including cumbersome and destructive in the past,the cucumber leaf disease severity real-time detecting system based on Android was developed.The iterative threshold segmentation was used to separate the leaf area from background.The fuzzy C-means cluster algorithm was adopted to extract the disease spots and the ratio kbetween the leaf disease spots pixels number and the leaf area pixels number was attained.The cucumber leaf disease severity was determined according to relevant standards,and the SQLite database was used to add other cucumber disease grading standards and prevention and control measures dynamically.The cucumber leaf disease severity and the prevention and control measures were displayed on the screen of mobile phone.Experimental results show that the proposed system can be used to real-time detect the cucumber leaf disease non-destructively in the fields,and determine the leaf disease severity accurately and quickly.
分 类 号:TP391.4[自动化与计算机技术—计算机应用技术]
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