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Application of machine vision to human shape analysis techniques in leaf and plant identification: An intelligent vision structure.

机译:机器视觉在叶片和植物识别中的人体形状分析技术中的应用:一种智能的视觉结构。

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摘要

Intelligent vision systems capable of automatically interpreting images are the next generation in machine vision. These systems will be functional to nonexperts in the machine vision field, and will be flexible and reprogrammable for general use. Addition of intelligence into vision systems requires an understanding and structuring of human visual and scene interpretation techniques.;This research was designed to investigate the interrelationships and combine the areas of image processing, feature extraction and techniques of human scene interpretation. The research is especially unique in its rule-based structuring of subjective, qualitative human-level shape features and quantitative machine-level shape features. Additionally a unique approach was implemented to extract plant/leaf shape features using information gathered from critical points along object borders. The critical points were determined using the object's centroid. The image processing portion of the program followed a procedural format with examples of images processed by various routines displayed on a screen for user evaluation, which allowed the system to act as a programming aid.
机译:能够自动解释图像的智能视觉系统是机器视觉的下一代。这些系统将对机器视觉领域的非专家发挥作用,并且对于一般用途将是灵活且可重新编程的。将智能添加到视觉系统需要对人类视觉和场景解释技术的理解和构建。本研究旨在研究相互关系,并将图像处理,特征提取和人类场景解释技术领域结合起来。该研究在基于规则的主观,定性人类水平形状特征和定量机器水平形状特征的结构方面尤其独特。此外,还采用了一种独特的方法,利用从沿对象边界的关键点收集的信息来提取植物/叶子的形状特征。临界点是使用对象的质心确定的。程序的图像处理部分遵循程序格式,在屏幕上显示了由各种例程处理的图像示例,以供用户评估,从而使系统可用作编程辅助工具。

著录项

  • 作者

    Guyer, Daniel Earl.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Engineering Agricultural.;Artificial Intelligence.
  • 学位 Ph.D.
  • 年度 1988
  • 页码 223 p.
  • 总页数 223
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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