基于计算机图像处理的稻米垩白测定系统的研究  

Studies on measurement system for rice chalkiness based on computer image processing

作　　者：陈丁山 程鹏[1,2] 李东晖[3] 萧浪涛[1,2] 

机构地区：[1]植物激素与生长发育湖南省重点实验室,湖南长沙410128 [2]湖南省作物种质创新与资源利用重点实验室,湖南长沙410128 [3]湖南农业大学信息科学技术学院,湖南长沙410128

出　　处：《湖南农业大学学报（自然科学版）》2011年第5期469-473,共5页Journal of Hunan Agricultural University(Natural Sciences)

基　　金：国家自然科学基金项目(30600049)

摘　　要：基于Chalkiness V1.0,以Visual C++.NET为开发工具,设计开发计算机图像处理系统Chalkiness V2.0,专用于NY147—88标准中优质稻米分级质量指标垩白粒率、垩白度和粒型等参数的检测。系统由图像数据预处理模块、样品识别模块、垩白识别模块、长宽比识别模块、统计分析模块和输出模块组成。运用该系统测定丰源B、密阳46和日本晴等3个水稻品种稻米垩白指标,只需1次图像分析即可输出垩白粒率、垩白度、投影面积等参数。Based on Chalkiness Vl.0, using Visual C＋＋.NET as tools, a computer image processing system ChalkinessV2.0 has been developed for the detection of chalky rice rate, chalkiness degree and grain shape for grading of the high quality rice required by the national standard NY147-88. The system is composed of modules of image preprocessing, sample identification, chalkiness distinguishing, ratio of length and width detection, statistics and analysis and results export. The system can analyze the rice chalkiness of three rice varieties： Fengyuan B, Miyang 46 and Nipponbare. Chalky scores such as chalky rice rate, chalkiness degree and projected area can be gotten with parameters imported only once.

关 键 词：稻米 垩白指标 图像处理 快速检测 

分 类 号：S511.01[农业科学—作物学] TP317.4[自动化与计算机技术—计算机软件与理论]