摘要 | 针对竹材定长截断设备自动化程度低的现状, 提出一种基于软件运动控制的竹材截断控制方案, 并应用图像处理技术集成设计了竹节识别系统, 使竹材加工过程中能有效避开竹节。首先, 经灰度处理、滤波去噪, 获得平滑后的图像; 其次, 利用开运算和膨胀等形态学操作, 提取竖线特征; 最后, 通过对直线边缘检测得到的线段进行优化筛选, 计算判断预截断区域竹节是否存在。实验结果表明, 竹节识别准确率可达到90%, 识别效率高, 可满足竹材定长生产需求。 |
Abstract | In view of the low automation degree of bamboo fixed-length truncation equipment, this paper proposes a bamboo truncation control scheme based on software motion control, and uses image processing technology to integrate and design the bamboo joint identification system, which can effectively avoid opening and cutting bamboo joints during processing. Firstly, the smoothed image is obtained by grayscale processing, filtering and denoising; secondly, vertical line features are extracted by morphological operations such as opening operation and dilation; finally, by optimizing and screening the line segments obtained by the line edge detection, it is calculated and judged whether there is a bamboo joint in the pre-truncated area. The experimental results show that the accuracy rate of bamboo joint recognition of the system can reach 90%, and the recognition efficiency is high, which can meet the needs of fixed-length production of bamboo. |
DOI | 10.48014/fcmet.20220422001 |
文章类型 | 研究性论文 |
收稿日期 | 2022-04-22 |
接收日期 | 2022-06-19 |
出版日期 | 2022-06-28 |
关键词 | 竹节识别, 机器视觉, 智能化, 集成化 |
Keywords | Bamboo joint identification, machine vision, intelligence, integration |
作者 | 苏坚毅, 王振忠*, 陈永明 |
Author | SU Jianyi, WANG Zhenzhong*, CHEN Yongming |
所在单位 | 厦门大学机电工程系, 厦门 361005 |
Company | Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361005, China |
浏览量 | 996 |
下载量 | 346 |
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引用本文 | 苏坚毅, 王振忠, 陈永明. 基于图像处理的竹材定长截断系统研究[J]. 中国机械工程技术学报, 2022, 1(1): 1-7. |
Citation | SU Jianyi, WANG Zhenzhong, CHEN Yongming. Research on fixed-length truncation system of bamboo based on image processing[J]. Frontiers of Chinese Mechanical Engineering and Technology, 2022, 1(1): 1-7. |