计算机与现代化

• 图像处理 • 上一篇    下一篇

基于机器视觉的非接触式马体尺测量方法

  

  1. (新疆农业大学计算机与信息工程学院,新疆乌鲁木齐830052)
  • 收稿日期:2019-03-14 出版日期:2019-10-28 发布日期:2019-10-29
  • 作者简介:买尔孜燕古丽·阿不都拉(1992-),女(维吾尔族),新疆吐鲁番人,硕士研究生,研究方向:农业信息化技术,E-mail: 1650230293@qq.com; 冯向萍(1973-),女,副教授,博士,研究方向:软件工程,数据库,E-mail: fxp@xjau.edu.cn。
  • 基金资助:
    新疆维吾尔自治区重大科技专项(2017A01002-5)

Non-contact Horse Body Measurement Method Based on Machine Vision

  1. (College of Computer and Information Engineering, Xinjiang Agricultural University, Urumqi 830052, China)
  • Received:2019-03-14 Online:2019-10-28 Published:2019-10-29

摘要: 目前马体尺测量方法是直接接触测量,此方法不仅耗费大量的人力、财力,而且操作步骤繁琐。本文首先总结归纳测量马体体尺的方法,其次对这些年来已有的畜牧体尺测量方法进行综述,阐述马体体尺测量方法的主要内容,并对马体体尺测量方法进行展望。本文对10匹不同年龄的雌性马图像进行灰度化、去噪、阈值化分割、提取轮廓等图像预处理,进行图像角点检测,标识出轮廓边缘的所有交点,再利用像素遍历识别出马体的关键点,如肩甲点、前脚点、胸骨前缘点、臀部点、臀部最高点等;同时运用海伦秦九韶公式和几何关系计算方法,计算出马体的体高、体长等数据。通过运用此方法测量得出,马体体长平均相对误差为3.97%,马体体高平均相对误差为4.45%。此方法为马体体尺研究者提供了科学的研究依据。

关键词: 机器视觉, 图像处理, 角点检测, 像素遍历, 体尺测量

Abstract: At present, the method of horse body measurement refers to the direct contact measurement, which not only consumes lots of manpower and financial resources, but also has the complicated operational steps. In this thesis, the methods of measuring the horse body size are summarized, the methods of herding body size measurement in recent years are reviewed, the main contents of horse body size measurement method are elaborated, and the horse body measurement method is prospected. The paper conducts graying, denoising, thresholding cutting and profile extraction for figures of 10 female horses with different ages, then conducts the image corner detection, and identifies all nodes on the margin of outline, and then uses the pixel traversal to identify the key points of the horse body, including scapula point, forefoot point, sternum front edge point, haunch point and highest haunch point. At the same time, Helon-Qin Jiushao’s formula and geometrical relationship method are used to calculate height and length of the horse body. Such a method is used to measure the average relative error of the horse body length as 3.97% and average relative error of the horse body height as 4.45%. This method provides a scientific research basis for scholars to study the horse body size.

Key words: machine vision, image processing, corner detection, pixel traversal, body measurement

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