基于计算机图像处理的番茄叶片基角自动提取与测量
首发时间:2013-04-19
摘要:叶片基角是表征温室番茄植株生长形态的重要特征,应用计算机图像处理技术研究开发了番茄叶片基角的自动提取与测量方法。通过对图像颜色空间变换,选取了HSV彩色空间中S分量灰度图像对番茄植株进行分析。应用Otsu阈值分割算法对番茄植株进行了分割,进一步采用"中值滤波+闭-开运算"算法对分割后的二值图像进行滤波,经细化运算获取了番茄植株茎干的基本信息。提出了基于邻域搜索的番茄植株主茎与叶柄及二者交点的图像分析方法,基于最小二乘法实现了茎干直线拟合,并提取和计算了叶片基角参数。研究结果表明,番茄植株叶片基角的图像测量结果与手工测量结果呈线性相关,R2为0.9857。研究可为自动测量和分析番茄生长形态参数提供技术支持。
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Measurement of tomato leaf base angle using computer image processing
Abstract:In order to measure the morphological characteristics of crop non-destructively, the leaf base angle of tomato plant was measured using image processing. The image of tomato plant was acquired in greenhouse and the image processing algorithm was discussed following color space transformation, image segmentation, binary image filtering, straight line fitting and the angle calculation. Firstly, the RGB image was transformed to HSV color space, the Saturation image was selected to analysis the image. Secondly, Otsu method was applied to segment the tomato plant. Thirdly, the binary image of plant was filtered. A good result was gained by combination the median filtering and close-open morphological method. After image thinning, a method based on the number of adjacent points was designed to find the intersection of main stem and branches. Then, the stems of the plant were simulated by straight lines based on least squares method. The angle between main stem and branch was calculated. The experiment result showed that there was linear relationship between the calculated data by image processing technology and manual measurement with R2=0.9857. It provided a method for the automatic measurement and analysis of tomato growth.
Keywords: Image processing base angle tomato growth status.
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