Cotton image segmentation based on K-means clustering and marker watershed

ZHANG Xinliang; XIA Yafei; XIA Nan; ZHAO Yunji

doi:10.13873/J.1000-9787(2020)03-0147-03

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Cotton image segmentation based on K-means clustering and marker watershed

更新时间：2025-09-11

- Cotton image segmentation based on K-means clustering and marker watershed
- Issue 3, Pages: 147-149(2020)
- 作者机构：
  
  1. 河南理工大学电气工程与自动化学院
  2. 安阳钢铁集团有限责任公司
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2020)03-0147-03
  CLC： S562;TP391.41
- Published：2020
- 稿件说明：
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ZHANG Xinliang, XIA Yafei, XIA Nan, et al. Cotton image segmentation based on K-means clustering and marker watershed[J]. 2020, (3): 147-149.
DOI：

ZHANG Xinliang, XIA Yafei, XIA Nan, et al. Cotton image segmentation based on K-means clustering and marker watershed[J]. 2020, (3): 147-149. DOI： 10.13873/J.1000-9787(2020)03-0147-03.

摘要

针对棉花识别中由于光照不均、背景复杂等不利影响降低识别率的问题

提出了一种基于K均值聚类与标记分水岭的棉花图像分割算法。基于棉花和背景在颜色上的信息差别

使用K均值聚类算法将复杂背景棉花分成棉叶、棉花、土壤和棉枝四类。进一步

基于棉花和背景在亮度上的信息差异

利用二维Otsu算法对棉花目标初次分割

并通过标记分水岭算法完成目标识别。通过实验验证:改进的标记分水岭算法能够有效解决棉花目标的过分割问题

显著提高了识别率

同时该方法对具有同类特征的花卉采摘视觉系统的设计具有参考价值。

Abstract

A cotton image segmentation algorithm based on K-means clustering and marking watershed is proposed to solve the problem of low cotton recognition affected by uneven illumination and complex background.Based on the difference of color information between cotton and background

K-means clustering algorithm is used to classify cotton with complex background into four categories: cotton leaf

cotton

soil and cotton branch.Furthermore

based on the difference of brightness between cotton and background

two-dimensional Otsu algorithm is used to segment the cotton target for the first time

and marked-based watershed algorithm is used to complete the target recognition. Experiments show that the improved marked-based watershed algorithm can effectively solve the problem of over-segmentation of cotton targets

and significantly improve the recognition rate. At the same time

this method has reference value for the design of flower picking vision system with similar characteristics.

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