Research on method of reinforcement count based on neural network

CHEN Zhi-kun1; PAN Xiao-di1; WANG Fu-bin1; ZHOU Ya-luo1; LIU Jie2

doi:10.13873/j.1000-97872010.08.022

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Research on method of reinforcement count based on neural network

更新时间：2025-09-11

- Research on method of reinforcement count based on neural network
- Vol. 29, Issue 8, Pages: 44-47(2010)
- 作者机构：
  
  1. 河北理工大学计算机与自动控制学院
  2. 东北大学机械工程与自动化学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872010.08.022
  CLC： TP391.41
- Published：2010
- 稿件说明：
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[1]陈至坤,潘晓娣,王福斌,周亚罗,刘杰.基于神经网络的钢筋计数方法研究[J].传感器与微系统,2010,29(08):44-47.

CHEN Zhi-kun1, PAN Xiao-di1, WANG Fu-bin1, et al. Research on method of reinforcement count based on neural network[J]. 2010, 29(8): 44-47.
[1]陈至坤,潘晓娣,王福斌,周亚罗,刘杰.基于神经网络的钢筋计数方法研究[J].传感器与微系统,2010,29(08):44-47. DOI： 10.13873/j.1000-97872010.08.022.

CHEN Zhi-kun1, PAN Xiao-di1, WANG Fu-bin1, et al. Research on method of reinforcement count based on neural network[J]. 2010, 29(8): 44-47. DOI： 10.13873/j.1000-97872010.08.022.

摘要

为了提高钢筋的计数准确率和效率

综合运用图像处理技术和神经网络技术

实现对钢筋的识别和计数。对获取的钢筋原始图像进行数字图像处理

得到感兴趣的部分即钢筋的轮廓;计算单根钢筋轮廓的宽度、高度、面积和打捆钢筋的总面积4个特征量;将这4个特征量作为神经网络的输入

训练网络识别钢筋并计数。仿真实验验证了这种方法的可行性和有效性。

Abstract

In order to improve the counting accuracy and efficiency

the image processing techniques and neural network technology are integrated used to realize the identification and counting of the steel bar.The obtained original image of the steel bar is image processed digitally to obtain the interested part which is the the outline of reinforcement.calculate the width

height

area of a single steel bar contour and the total area of four bundled steel bar.These four characteristic quantities act as neural network input

the network is trained to recognize and count reinforcement.Simulation results verify the feasibility and effectiveness of this method.

关键词

Keywords

references

一种基于图像处理的成捆钢筋计数方法 [J]. 罗山,黄欢,刘继红. 微计算机应用 . 2008(06)

模板匹配技术在焊缝图像处理中的应用 [J]. 刘国平,王洪亮,胡荣华,徐明,张华. 焊接技术 . 2004(04)

一种计算任意形状封闭区域面积的新方法 [J]. 李波,刘东华,梁光明,唐朝京. 国防科技大学学报 . 2002(04)

MATLAB神经网络仿真与应用[M]. 科学出版社 , 闻新等编著, 2003

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