Please wait a minute...
吉林化工学院学报, 2023, 40(1): 68-73     https://doi.org/10.16039/j.cnki.cn22-1249.2023.01.015
  本期目录 | 过刊浏览 | 高级检索 |
基于机器视觉的点阵字符分割方法
李百明
黎明职业大学 智能制造工程学院,福建 泉州 362000
Segmentation Method of Dot Matrix Character Based on Machine Vision
LI Baiming

下载:  PDF (4790KB) 
输出:  BibTeX | EndNote (RIS)      
摘要 

针对点阵喷码字符因背景复杂、局部漏喷或字符模糊等原因导致字符识别率低的问题,提出了一种基于机器视觉的点阵字符分割方法。首先,利用Blob分析从图像中快速定位出点阵字符所在矩形区域,并将其旋转到水平方向;然后,采用水平灰度投影法将该矩形区域分割成两行,再采用垂直灰度投影法结合字符宽度特征将每行中的字符分割开来;最后,将分割出的字符送入MLP分类器进行识别。实验结果显示,该方法的分割准确率为98.7%,显著优于现有的分割方法,且还具有较强的识别通用性;因此,该方法在点阵字符识别方面具有良好的应用价值。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
李百明
关键词:  点阵字符  Blob分析  灰度投影     
Abstract: 

A dot matrix character segmentation method based on machine vision was proposed to address the low recognition rate of dot matrix characters caused by complex backgrounds, local leakage, or blurred characters. First, the rectangular area where the dot matrix characters were located was quickly located from the image using Blob analysis and rotated to the horizontal direction. Then, the rectangular area was segmented into two rows using horizontal grey scale projection, and the characters in each row were segmented using vertical grey scale projection combined with character width features. Finally, the segmented characters were fed into the MLP classifier for recognition. The experimental results show that the segmentation accuracy of the method is 98.7%, which is significantly better than existing segmentation methods, and also has strong recognition generality; therefore, the method has good application value in the recognition of dot matrix characters.

Key words:  dot matrix character    Blob analysis    grey projection
               出版日期:  2023-01-25      发布日期:  2023-01-25      整期出版日期:  2023-01-25
TP391  
引用本文:    
李百明. 基于机器视觉的点阵字符分割方法 [J]. 吉林化工学院学报, 2023, 40(1): 68-73.
LI Baiming. Segmentation Method of Dot Matrix Character Based on Machine Vision . Journal of Jilin Institute of Chemical Technology, 2023, 40(1): 68-73.
链接本文:  
https://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2023.01.015  或          https://xuebao.jlict.edu.cn/CN/Y2023/V40/I1/68
[1] 余鹏泽 , 刘兴德 , 谢延楠 , 任洛莹 , 孔志成 , 胡文松. MSP-YOLO:用于识别水果的改进算法[J]. 吉林化工学院学报, 2024, 41(7): 18-25.
[2] 都芳芳, 甘树坤, 吕雪飞. 基于优化的SURF图像拼接算法的研究[J]. 吉林化工学院学报, 2024, 41(7): 86-91.
[3] 王影, 孙可欣, 刘振刚, 高康盛, 刘麒. 基于改进YOLOv5的仿生机器鱼目标检测算法研究[J]. 吉林化工学院学报, 2024, 41(5): 22-29.
[4] 李双远, 刘向阳. 基于改进的Faster R-CNN算法建筑领域裂缝检测研究[J]. 吉林化工学院学报, 2024, 41(5): 50-53.
[5] 姜春雨, 王伟. 基于类别查询的视觉Transformer研究[J]. 吉林化工学院学报, 2024, 41(3): 62-67.
[6] 王辅民, 周红娟, 冯国亮, 邢雪. 基于特征融合的空压机故障诊断算法研究[J]. 吉林化工学院学报, 2024, 41(3): 37-41.
[7] 崔世磊, 孙明革, 高聪, 郭晓龙, 李迎岗. 基于YOLOv7的番茄检测算法优化与实现[J]. 吉林化工学院学报, 2024, 41(3): 25-30.
[8] 王 影, 王 晨, 贾永涛, 刘 麒. 基于改进YOLOv5s的仓储货物检测算法研究[J]. 吉林化工学院学报, 2024, 41(1): 51-58.
[9] 王军. 基于LiteOS系统的串行数据通信的研究与应用 [J]. 吉林化工学院学报, 2024, 41(1): 86-90.
[10] 任洛莹 , 刘兴德 , 谢延楠 , 胡文松 , 余鹏泽, 孔志成. CGB-YOLO:用于检测钢铁表面缺陷的YOLO算法 [J]. 吉林化工学院学报, 2023, 40(11): 38-44.
[11] 赵梦瑶, 朱建军. 基于三维点云的机械臂抓取位姿检测方法 [J]. 吉林化工学院学报, 2023, 40(11): 54-60.
[12] 周志成 , 李艺谋, 杜宪华, 吴文豪. 高校智慧校园数据治理的研究与应用 [J]. 吉林化工学院学报, 2023, 40(11): 84-88.
[13] 李百明. 基于机器视觉的角码孔径测量方法研究 [J]. 吉林化工学院学报, 2023, 40(7): 77-82.
[14] 刘麒, 盛德庆, 孙万龙, 王影.

基于改进YOLOv5s的水果目标检测研究 [J]. 吉林化工学院学报, 2023, 40(7): 34-41.

[15] 范家墁. 数字化背景下基于深度学习的生成设计在视觉识别平台中的应用研究 [J]. 吉林化工学院学报, 2023, 40(3): 62-67.
[1] . [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 0 .
[2] . [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 0 .
[3] SHAO Bao-li, LU Da, ZHAO Dong-hui. The Application of Dimensional Analysis in the Physical Quantity Conversion between Physical System and Numerical System [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 1 -3 .
[4] ZHANG Jian, ZHAO Xiang, QU Bo, WU Qi, LIU Yu-tong, LI Yu-shi, LIU Qun. Application of Phosphorus-sulfur-nitrogen Composite Flame Retardant in Cotton Fabric [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 4 -7 .
[5] WU Ping, REN Hong, LU Fei, WEI Qingling. A Functional Material on Recognition of Zn(II) ions based on the New Azo Compound [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 8 -10 .
[6] YANG Yan-jun, WANG Ya-hong, Yang Xiu-dong. Process Aptimization of Surfactant Assisted Extraction of Total Polyphenols from Kyllinga Brevifolia Rottb [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 11 -15 .
[7] LIU Jin-lu, LEI Yong-ping, WANG xiao-lin, ZHONG fang-li. Study on the  Purification Method of Total Saponins fromFruit of Rosa Davuvrica Pall. and its  Purification Method [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 16 -23 .
[8] SONG Jian-gang, ZHONG Fang-li, WANG Xiao-lin, LIN Yu. Study on Extraction of Anthocyanin from Aronia melanocarpa Fruit by Ionic liquid Ultrasound Assisted [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 24 -31 .
[9] TAN Li-hui, TAN Hong-wu. The Crashworthiness Analysis of different Cross-Section Thin-Walled Components [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 32 -35 .
[10] YU Wen-xin, ZHENG Kai, WANG Li-hui, LIU Hai-bo, Wang Jian-xin. The Influence of Magnetostrictive Transducer Radiation Plate material on Radiation Sound Field Distribution [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 36 -40 .
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed