This paper presents an approach to segment the light microscopic images of hardwood species and then extract only the vessel elements out of the images. In this work, an effort was made to propose a platform-independent tool based on simple digital image processing technique to quantify wood conduits (especially vessel elements at present). A prototype model was developed and tested on several microscopic images prepared at the xylarium (DDw) of the Wood Anatomy Discipline of the Forest Research Institute, Dehradun, India. The investigation of the experimental work suggests that for most of the images, with the help of appropriate parameter selection, the vessel elements were extracted. In one case, the identified vessel element area was in fact the area of vessel element plus the surrounding parenchyma elements area. Close observation of the aforementioned object in original color (RGB) image suggests that the parenchyma elements surrounding the vessel elements have higher intensity level, in contrast to other parenchyma elements. This happened because an intensity-based thresholding approach was used for converting an RGB image to a binary image. Further, along with the extraction of vessel elements, the proposed model is capable of computing the hydraulic conductivity and lumen resistivity of the vessel elements.

中文翻译：

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使用数字图像处理技术确定阔叶树种图像的容器元素和水力传导率

本文提出了一种对硬木树种的光学显微图像进行分割，然后仅从图像中提取血管元素的方法。在这项工作中，努力提出一种基于简单数字图像处理技术的平台独立工具，以量化木材管道（尤其是目前的容器元素）。在印度德拉敦森林研究所木材解剖学 (DDw) 的 xylarium (DDw) 准备的几张显微图像上开发并测试了原型模型。实验工作的调查表明，对于大多数图像，在适当的参数选择的帮助下，提取了血管元素。在一种情况下，识别的血管元素面积实际上是血管元素面积加上周围薄壁组织元素面积。在原始颜色 (RGB) 图像中仔细观察上述对象表明，与其他薄壁组织元素相比，血管元素周围的薄壁组织元素具有更高的强度水平。发生这种情况是因为使用了基于强度的阈值方法将 RGB 图像转换为二值图像。此外，随着血管元素的提取，所提出的模型能够计算血管元素的水力传导率和管腔电阻率。