基于安卓的黄瓜叶部病害程度检测系统的研发

Developing detecting system for cucumber leaf disease severity based on Android

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.