基于残差网络的字符编码标志点识别
Recognition of Character Coded Marks Based on Residual Network
菲劳拉·吐尔洪江 1古丽巴哈尔·托乎提 1买买提明·艾尼 2补生来 1吴志强1
作者信息
- 1. 新疆大学机械工程学院,乌鲁木齐 830017
- 2. 新疆大学机械工程学院,乌鲁木齐 830017;佰博机电科技有限公司,乌鲁木齐 830011
- 折叠
摘要
针对大尺寸结构近景摄影测量中如何提高编码标志的容量和识别率等问题,设计了一种由中心圆,字母和数字组成的字符编码标志,提出了一种基于ResNet18 模型改进的字符编码点识别方法和基于Zernike矩提出的亚像素定位方法.首先,利用均值滤波、自适应阈值处理和形态学中的闭运算等方法对图像进行预处理,根据连通域分析与筛选对预处理好的图像进行分割得到字符编码点;其次,用字符编码点识别网络进行识别,最终通过亚像素定位方法对编码点进行定位.从实验结果得出字符编码点的识别准确率可达 99.89%.该类标志点定位精度高,提出的识别方法准确率高.
Abstract
Aiming at the problem of how to improve the capacity and recognition rate of coded mark in close-range photogrammetry of large structure,this paper designs a character coded marks composed of cen-ter circle,letters and numbers,and proposes a character coded point recognition method based on ResNet18 model and a sub-pixel location method based on Zernike moment.Firstly,the image is preprocessed by means filtering,adaptive threshold processing and closing operation in morphology,and then the prepro-cessed image is segmented according to connected domain analysis and screening to get character coded marks.Secondly,the character coded mark recognition network is used for recognition,and finally the cod-ing points are located by subpixel positioning method.The experimental results show that the recognition accuracy of character coding points can reach 99.89%.This kind of marker points have high positioning accuracy and the proposed recognition method has high accuracy.
关键词
近景摄影测量/字符编码标志/字符编码点识别网络/亚像素定位Key words
close-range photogrammetry/character coded marks/character coded marks recognition net-work/subpixel localization引用本文复制引用
基金项目
国家自然科学基金资助项目(12162031)
出版年
2024
NETL
NSTL
万方数据