湖北农业科学 ›› 2023, Vol. 62 ›› Issue (8): 197-201.doi: 10.14088/j.cnki.issn0439-8114.2023.08.031

• 信息工程 • 上一篇    下一篇

基于欧拉数的谷物颗粒图像目标计数方法

康世英1, 姚斌2   

  1. 1.咸阳师范学院计算机学院,陕西 咸阳 712000;
    2.陕西科技大学电子信息与人工智能学院,西安 710021
  • 收稿日期:2022-05-23 出版日期:2023-08-25 发布日期:2023-09-22
  • 作者简介:康世英(1980-),女,山西大同人,讲师,主要从事计算机视觉、图像处理研究,(电话)15991889141(电子信箱)kangsying@126.com。
  • 基金资助:
    国家自然科学基金项目(61603234)

Target counting method of grain particle images based on Euler numbers

KANG Shi-ying1, YAO Bin2   

  1. 1. School of Computer Science, Xianyang Normal University, Xianyang 712000,Shaanxi,China;
    2. School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an 710021,China;
  • Received:2022-05-23 Online:2023-08-25 Published:2023-09-22

摘要: 为了解决谷物选育品种过程中人工计数存在的操作费时、精度不高等问题,提出一种利用计算机处理谷物颗粒图像进行计数的方法。首先对所采集到的谷物颗粒图像进行二值化,将图像中背景和目标区域分开;然后对图像进行形态学运算、目标分割等预处理,最大程度减少图像中的谷物颗粒黏连现象;在最终的计数环节,为了提高计数速度,基于经过预处理后的谷物颗粒图像没有孔洞这一重要特征,利用图像欧拉数算法代替传统的连通域标记算法实现计数工作。结果表明,利用图像欧拉数算法的计数结果与利用传统连通域标记算法的计数结果完全一致,但在计数速度方面,利用图像欧拉数算法进行计数明显优于传统的连通域标记算法。

关键词: 欧拉数算法, 谷物颗粒图像, 计数方法

Abstract: In order to solve the problems of time-consuming and low accuracy in manual counting during the process of grain breeding, a method of counting using computer processing of grain particle images was proposed. Firstly, the collected grain particle images was binarized to separate the background and target regions in the image; then morphological operations, object segmentation, and other preprocessing on the image were performed to minimize the phenomenon of grain particle adhesion in the image; in the final counting link, in order to improve the counting speed, based on the important feature that the grain particle images had no holes after preprocessing, the image Euler numbers algorithm was used to replace the traditional connected domain marking algorithm to achieve the counting work.The results showed that the counting result of the image Euler numbers algorithm was completely consistent with that of the traditional connected domain labeling algorithm, but the counting speed of the image Euler numbers algorithm was obviously better than that of the traditional connected domain labeling algorithm.

Key words: Euler numbers algorithm, grain particle images, counting method

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