Extraction of plant parenchyma by computer image processing technology

Abstract

People are increasingly using different kinds of plant products, such as wood, but there are many kinds of wood and it is difficult to analyze and identify them, so how to use auxiliary equipment to analyze wood and achieve the goal of accurate wood identification without damaging the product itself has become one of the important problems to be solved in the field of wood research. The axial thin-walled tissue has important wood grain information and it is one of the important features for wood identification. In this paper, we studied the microscopic images of broadleaf wood, and obtained the microstructure images of wood cross-section by photographing, and extracted the complete axial thin-walled tissue morphology of wood by using computer image processing technology and other ways about computer vision. Firstly, the axial thin-walled wood images were de-noised to eliminate some noise effects, so as to facilitate the separation of the axial thin-walled wood; then the images were processed by mathematical morphology to successfully extract the axial thin-walled wood and duct morphology from the cross-sectional images of broadleaf wood; finally, the axial thin-walled wood was separated from the duct by calculating the area of the closed area.

Plant phenotyping relevance

木材横断面画像から軸方向柔組織と道管の形態・面積を抽出する画像処理手法が研究の中心であり、植物組織形態という観測可能な形質を取得している。

Code and data availability

The supplied blocks describe wood micrograph acquisition and MATLAB-based image processing, but contain no public dataset, image deposit, code release, or availability statement for the paper's phenotyping assets.

No evidence-backed public reproduction asset is currently recorded.