摘要
针对传统投影分割方法在提取单个数码管数字图像时过于依赖图像二值化及图像倾斜校正效果的问题,采用一种基于轮廓提取和轮廓排序相结合的数码管图像分割方法,实验证明该方法相比投影分割法在对数字区域的分割成功率上提高了13.5%;针对传统穿线法对数码管数字1识别度较低和机器学习算法运行用时较长的问题,提出一种基于六段数码管特征的改进穿线法与HOG+SVM方法相结合的数码管数字识别方法,该方法对数码管数字的识别准确率比传统穿线法提高了约4.5%,且平均运行时间仅为HOG+SVM方法的1/5。实验结果证明了这种方法在进行数码管读数时的可靠性和优越性。
In traditional projection method when rely too much on a single digital image are extracted image binarization and tilt correction effect problem,using a method based on contour extraction and contour sort of digital image segmentation method,experimental results show this method is compared with the projection segmentation on the success rate for segmenting the digital area increased by 13.5%;Against traditional threading method for number 1 low recognition and machine learning algorithms run takes longer problem,put forward an improved,based on the six characteristics of segment digital tube threading method and the HOG+SVM method with the combination of digital identification method,the method of digital tube digital identification accuracy than traditional threading method by about 4.5%,and the average elapsed time only 1/5 ofthe HOG+SVM method.The experimental results show the reliability and effectiveness of the method in digital tube reading.
作者
宋一言
唐东林
吴续龙
周立
秦北轩
SONG Yi-yan;TANG Dong-lin;WU Xu-long;ZHOU Li;QIN Bei-xuan(School of Mechanical and Electrical Engineering,Southwest Petroleum University,Chengdu 610500,China)
出处
《计算机科学》
CSCD
北大核心
2021年第S02期396-399,440,共5页
Computer Science
基金
四川省科技支撑计划项目(2017FZ0033)。
关键词
数码管
识别和读数
图像处理
轮廓分割
穿线法
HOG+SVM
Digital tube
Identifying and reading
Image processing
Contour segmentation
Stringing method
HOG+SVM
