Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (11A): 396-399.doi: 10.11896/jsjkx.210100123

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Study on Digital Tube Image Reading Combining Improved Threading Method with HOG+SVM Method

SONG Yi-yan, TANG Dong-lin, WU Xu-long, ZHOU Li, QIN Bei-xuan   

  1. School of Mechanical and Electrical Engineering,Southwest Petroleum University,Chengdu 610500,China
  • Online:2021-11-10 Published:2021-11-12
  • About author:SONG Yi-yan,born in 1997,M.S.student.His main research interests include image processing,deep learning and target detection.
    TANG Dong-lin,born in 1970,Ph.D,doctoral supervisor.His mian research interests include nondestructive testing and pattern recognition technology.
  • Supported by:
    Sichuan Science and Technology Support Plan Project(2017FZ0033).

PDF (PC)

707

Abstract: 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.

Key words: Contour segmentation, Digital tube, HOG+SVM, Identifying and reading, Image processing, Stringing method

CLC Number: 

  • TP751
[1]CHEN G,HUZ Z F,ZHEN C.Fast recognition algorithm ofdigital instrument based on feature detection[J].The Chinese test,2019,45(4):150-154.
[2]CHEN Y.Research on the development and application dynamics of machine vision technology[J].Wireless Interconnection Technology.2018,15(19):147-148.
[3]CHEN X.Research on Automatic Detection System of Power Instrument Based on Machine Vision[D].Harbin:Harbin Institute of Technology,2015.
[4]DENG Q N,SHI X L.Indoor digital display instrument reading recognition of substation[J].Industrial Instrumentation and Automation,2018(2):86-89.
[5]HE W,XU G,RONG Z,et al.Automatic Calibration System for Digital-Display Vibrometers Based on Machine Vision[J].Metrology & Measurement Systems,2014,21(2):317-328.
[6]LIU Z,LUO Z,GONG P,et al.The research of character recognition alg-orithm for the automatic verification of digital instrument[C]//International Conference on Measurement,Information and Control.IEEE,2014:177-181.
[7]CHEN Z X.A digital display digital recognition al-gorithm[J].Computer Knowledge and Technology,2014,10(23):5496-5500.
[8]DING S,REN G Y,ZHANG F M.Improved threading method for caliper image recognition[J].Journal of Measurement,2019,40(5):765-769.
[9]DU B.Research on Instrumentation Positioning and Identifica-tion Method in Patrol Inspection System[D].Wuhan:Huazhong University of Science and Technology,2018.
[10]LIN J P,LIAO Y P.Automatic recognition of digital instrument reading based on OpenCV and LSSVM[J].Microcomputers and Applications,2017,36(2):37-40.
[11]LIU J.Research on Automatic Character Recognition of Digital Instrument Based on Image Processing[J].Information Technology,2020,341(4):84-88.
[12]CHEN J L.Detection method of concrete based on image processing method[J].Chinese Journal of Liquid Crystals and Displays,2020,35(4):395-401.
[13]CHEN Z B,ZHANG C,SONG Y.Application of GrayscaleStretch Retinex in Large-scale Smoke Image Enhancement[J].Infrared and Laser Engineering,20141 43(9):3146-3150.
[14]IEEE Xplore Abstract- A Threshold Selection Method fromGray-Level His-tograms[J].IEEE Transactions on Systems Man & Cybernetics,1979.
[15]DALAL N,TRIGGS B.Histograms of oriented gradients forhuman detec-tion[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVPR 2005).IEEE,2005,1:886-893.
[16]WANG L.Research on Vehicle Detection Algorithm Based on HOG and SVM[D].Wuhan:Huazhong University of Science and Technology,2017.
[1] LAI Teng-fei, ZHOU Hai-yang, YU Fei-hong. Real-time Extend Depth of Field Algorithm for Video Processing [J]. Computer Science, 2022, 49(6A): 314-318.
[2] LIU Wei-ye, LU Hui-min, LI Yu-peng, MA Ning. Survey on Finger Vein Recognition Research [J]. Computer Science, 2022, 49(6A): 1-11.
[3] ZHAN Rui, LEI Yin-jie, CHEN Xun-min, YE Shu-han. Street Scene Change Detection Based on Multiple Difference Features Network [J]. Computer Science, 2021, 48(2): 142-147.
[4] ZHANG Yu-long, WANG Qiang, CHEN Ming-kang, SUN Jing-tao. Survey of Intelligent Rain Removal Algorithms for Cloud-IoT Systems [J]. Computer Science, 2021, 48(12): 231-242.
[5] FENG Yi-fan, ZHAO Xue-qing, SHI Xin, YANG Kun. Light Superposition-based Color Constancy Computational Method [J]. Computer Science, 2021, 48(11A): 386-390.
[6] XIE Hai-ping, LI Gao-yuan, YANG Hai-tao, ZHAO Hong-li. Classification Research of Remote Sensing Image Based on Super Resolution Reconstruction [J]. Computer Science, 2021, 48(11A): 424-428.
[7] YAO Nan, ZHANG Zheng. Scar Area Calculation Based on 3D Image [J]. Computer Science, 2021, 48(11A): 308-313.
[8] CAI Yu-xin, TANG Zhi-wei, ZHAO Bo, YANG Ming and WU Yu-fei. Accelerated Software System Based on Embedded Multicore DSP [J]. Computer Science, 2020, 47(6A): 622-625.
[9] MA Hong. Fusion Localization Algorithm of Visual Aided BDS Mobile Robot Based on 5G [J]. Computer Science, 2020, 47(6A): 631-633.
[10] SONG Ya-fei, CHEN Yu-zhang, SHEN Jun-feng and ZENG Zhang-fan. Underwater Image Reconstruction Based on Improved Residual Network [J]. Computer Science, 2020, 47(6A): 500-504.
[11] MIAO Yi, ZHAO Zeng-shun, YANG Yu-lu, XU Ning, YANG Hao-ran, SUN Qian. Survey of Image Captioning Methods [J]. Computer Science, 2020, 47(12): 149-160.
[12] LING Chen, ZHANG Xin-tong, MA Lei. Remote Sensing Image Processing Technology and Its Application Based on Mask R-CNN Algorithms [J]. Computer Science, 2020, 47(10): 151-160.
[13] GUO Lan-ying, HAN Rui-zhi, CHENG Xin. Digital Instrument Identification Method Based on Deformable Convolutional Neural Network [J]. Computer Science, 2020, 47(10): 187-193.
[14] ZHU De-li, YANG De-gang, HU Rong, WAN Hui. Adaptive Multi-level Threshold Binaryzation Method for Optical Character Recognition in Mobile Environment [J]. Computer Science, 2019, 46(8): 315-320.
[15] PAN Wei-qiong, TU Juan-juan, GAN Zong-liang, LIU Feng. Low Light Images Enhancement Based on Retinex Adaptive Reflectance Estimation and LIPS Post-processing [J]. Computer Science, 2019, 46(8): 327-331.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.