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林业科学 ›› 2004, Vol. 40 ›› Issue (3): 162-166.doi: 10.11707/j.1001-7488.20040328

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计算机技术在苗木自动分级中的应用发展概况

赵学增 杨延竹 王伟杰 吴羡   

  1. 哈尔滨工业大学机械电子工程系,哈尔滨150001
  • 收稿日期:2001-11-22 修回日期:1900-01-01 出版日期:2004-05-25 发布日期:2004-05-25

Review on Computer Technology Application to Seedlings Automatically grading

Zhao Xuezeng,Yang Yanzhu,Wang Weijie,Wu Xian   

  1. Department of Mechantronics Engineering,Harbin Institute of Technology Harbin150001
  • Received:2001-11-22 Revised:1900-01-01 Online:2004-05-25 Published:2004-05-25

摘要:

对苗木自动分级技术发展进行了概要的评述。最早苗木自动分级技术只是对造林苗木的某些形态参数进行自动测量,发展至今,基于计算机视觉的苗木自动分级系统已得到广泛研究。本文指出苗木自动分级技术必将向全面化发展,苗木形态学特征的进一步完善和非形态学特征的引入是苗木自动分级技术研究的重要内容,因此,建立基于彩色图像和三维图像处理的新的计算机视觉系统,以获得更全面的苗木分级特征,将成为苗木分级领域内最具发展前景的课题。

关键词: 苗木分级, 自动测量, 计算机视觉, 图像处理

Abstract:

The gradation of seedlings is an important means for increasing the survival rate of seedlings in afforestation,which has important significance for planting trees and greening environment.The manual gradation of afforestation seedlings not only expends a lot of human resources,but also has a high intensity of labour and lower efficiency,so the automatic technolgy of seedling grading has been studied widely.The development of the automatic technology of seedling grading is reviewed briefly in this paper.The research on the automatic technology of seedling gradation was started with auto-measurement of some morphological characteristics.Now the automatic gradation system of seedlings based on computer vision has been studied.In the future,automatic gradation technology of seedlings will be more perfect.And improving seedling's morphological characteristics and applying new non-morphological characteristics in the automatic gradation technology of seedlings is the most important task in the further research.Therefore,new computer vision system based on color image processing and 3D image processing is brought forward in this paper as the most promising subject in this field.More comprehensive characteristics are considered in the new system and more accurate result will be achieved.

Key words: Seedling gradation, Auto-measurement, Computer vision, Image processing