小麦茎秆截面参数显微图像测量系统

小麦的抗倒性与其茎秆截面显微结构密切相关,茎秆微观结构的观测和分析对小麦遗传育种具有重要意义。研究了一种显微图像测量系统,用于精确测量小麦茎秆截面的主要参数。使用计算机、图像采集室、光学显微成像系统等搭建了硬件平台,并开发了算法软件。系统针对茎秆截面的颜色和结构特点,对显微图像进行预处理得到髓腔、厚壁的轮廓,再进行椭圆拟合以计算截面整体、髓腔和厚壁的几何参数。根据维管束结构的一致性,提出了一种具有尺度、平移和旋转不变性的模板匹配方法,用于在目标图像中识别维管束并统计数量。实验表明该自动化测量系统具有高通量和高精确度的优点,在作物重要资源的挖掘和群体遗传等研究中具有重要的价值。

Measurement System for Parameters of Wheat Stem Section Based on Microimage Processing

Lodging resistance of wheat is closely related to its stem section microstructure. Observation and analysis of stem microstructure are of great significance for the genetic breeding. A microscopic image measurement system was studied, which could be utilized to measure the main parameters of the wheat stem section accurately. The equipment including computer platform, image acquisition box and electronic microscopy imaging system etc. was used to build the hardware platform and the algorithm software was developed. According to the characteristics of the stem structure and color, the contours of both mechanical tissue and medullary cavity were obtained using image processing procedures. After then the geometrical parameters of the whole section, medullary cavity and sclerenchyma were calculated by the ellipses fitting. Based on the uniformity of the vascular bundle structure, an original template matching method was proposed. This method was invariant to scaling, translation and rotation, which was used to identify and count the vascular bundle in the target image. It showed that this automated measurement system was of high throughput and high precision. The system will play an important role in both the screening of important crops resources and population genetic research.