skip to main content
10.1145/3436369.3436475acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiccprConference Proceedingsconference-collections
research-article

Target Text Location for Vehicle Inspection Based on Template Matching

Published: 11 January 2021 Publication History

Abstract

Nowadays, vehicle inspection has an urgent demand for automatic target information recognition technology. Target text location is the prerequisite for target text recognition and has a great influence on recognition. Experimental results show that deep learning algorithms, such as faster RCNN, are not effective on such problems to some extent. Therefore, this paper adopted the method of template matching, took the vehicle license application form as the research subject, realized the target text location according to the relative location between the target texts in the image, and achieved satisfactory results. The application of this method on the driving license proves that it is a target text location technology that can be applied to document images with relatively fixed layout.

References

[1]
Wang Hongmei, Tao Tingting and Zhang Jingrong. (2020). On the digital construction of archives. Archives of electromechanical warships (03), 101--103.(in Chinese)
[2]
Zhou Feng & Zhang Huaxiong. (2019). Anti skew Chinese text image file recognition technology. Computer system applications (01), 32--37 (in Chinese)
[3]
Jiang Yanhu & Bai Shixue. (2008). Research on text information extraction from complex background images. Journal of Jiangxi Institute of Education (03), 18--21. (in Chinese)
[4]
R. Islam, M. R. Islam and K. HasanTalukder, "Rule Based Filtering Approach for Detection and Localization of Bangla Text from Scene Images," 2017 International Conference on Recent Trends in Electrical, Electronics and Computing Technologies (ICRTEECT), Warangal, 2017, pp. 139--144.
[5]
Leibin Guan and Jizheng Chu, "Natural scene text detection based on SWT, MSER and candidate classification," 2017 2nd International Conference on Image, Vision and Computing (ICIVC), Chengdu, 2017, pp. 26--30.
[6]
X. Ren, Y. Zhou, Z. Huang, J. Sun, X. Yang and K. Chen, "A Novel Text Structure Feature Extractor for Chinese Scene Text Detection and Recognition," in IEEE Access, vol. 5, pp. 3193--3204, 2017.
[7]
X. Jiang, J. Lian, Z. Xia, X. Feng and A. Hadid, "Fast Chinese character detection from complex scenes," 2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA), Oulu, 2016, pp. 1--4.
[8]
J. Zhang, K. Huang, Y. Yu and T. Tan, "Boosted local structured HOG-LBP for object localization," CVPR 2011, Providence, RI, 2011, pp. 1393--1400.
[9]
P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan. Object Detection with Discriminatively Trained Part Based Models. In TPMAI, 2010.
[10]
P. F. Felzenszwalb, R. B. Girshick, D. McAllester and D. Ramanan, "Object Detection with Discriminatively Trained Part-Based Models," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 9, pp. 1627--1645, Sept. 2010.
[11]
L. Zhu, Y. Chen, A. Yuille and W. Freeman, "Latent hierarchical structural learning for object detection," 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, 2010, pp. 1062--1069.
[12]
A. Vedaldi, V. Gulshan, M. Varma and A. Zisserman, "Multiple kernels for object detection," 2009 IEEE 12th International Conference on Computer Vision, Kyoto, 2009, pp. 606--613.
[13]
X. Wang, T. X. Han and S. Yan, "An HOG-LBP human detector with partial occlusion handling," 2009 IEEE 12th International Conference on Computer Vision, Kyoto, 2009, pp. 32--39.
[14]
[1] Yao Liping & pan Zhongliang. (2020). Face recognition method based on improved hog and LBP algorithm. Optoelectronic Technology (02), 114--118 + 124 (in Chinese)
[15]
X. Jiang, J. Lian, Z. Xia, X. Feng and A. Hadid, "Fast Chinese character detection from complex scenes," 2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA), Oulu, 2016, pp. 1--4.
[16]
S. Ren, K. He, R. Girshick and J. Sun, "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 6, pp. 1137--1149, 1 June 2017.
[17]
J. Redmon, S. Divvala, R. Girshick and A. Farhadi, "You Only Look Once: Unified, Real-Time Object Detection," 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, 2016, pp. 779--788.
[18]
Liu, Wei (UNC Chapel Hill, Chapel Hill, United States). SSD: Single shot multibox detector.: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v 9905 LNCS, p 21--37, 2016, Computer Vision - 14th European Conference, ECCV 2016, Proceedings
[19]
T. Lin, P. Goyal, R. Girshick, K. He and P. Dollár, "Focal Loss for Dense Object Detection," 2017 IEEE International Conference on Computer Vision (ICCV), Venice, 2017, pp. 2999--3007.
[20]
Chen Xiao. (2017). Research and application of document image location and information extraction technology (Master's thesis, Beijing University of Posts and Telecommunications) (in Chinese)
[21]
Lin Hanyang, Zhan Yongzhao & Chen Yuzhong. (2019). Rapid detection and recognition of motor vehicle license in complex scenes. Minicomputer system (05), 1076--1082. (in Chinese)
[22]
Jiang Chongyu, Lu Tongwei, min Feng, Xiong Hanying & Hu Jiwei. (2019). Invoice text detection and recognition method based on neural network. Journal of Wuhan University of Technology (06), 586--590. (in Chinese)
[23]
H. Zhu, T. Zhang, L. Yan and L. Z. Deng. Robust and fast Hausdorff distance for image matching. Optical Engineering, v 51, n 1, January 2012.
[24]
G. Venugopal, P. Merkle, D. Marpe and T. Wiegand, "Fast template matching for intra prediction," 2017 IEEE International Conference on Image Processing (ICIP), Beijing, 2017, pp. 1692--1696.
[25]
Huang Xiaohui (2012). Research and algorithm design of target detection based on image matching (Master's thesis, Shanghai Jiaotong University). (in Chinese)
[26]
X. Chen and T. -. Cham, "Learning feature distance measures for image correspondences," 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), San Diego, CA, USA, 2005, pp. 560--567 vol. 2.
[27]
Y. Wan and N. Wei, "A Fast Algorithm for Recognizing Translated, Rotated, Reflected, and Scaled Objects From Only Their Projections," in IEEE Signal Processing Letters, vol. 17, no. 1, pp. 71--74, Jan. 2010.
[28]
Tao Shuo. (2020). Fast adaptive image matching algorithm based on Improved SIFT. Journal of Heilongjiang Institute of Technology (Comprehensive Edition) (05), 92--96 (in Chinese)
[29]
Yan chunman, Hao Youfei, Zhang Di & Chen Jiahui. (2019). Image matching with optimal threshold prediction under mixed features. Computer engineering and Science (10), 1803--1808. (in Chinese)

Index Terms

  1. Target Text Location for Vehicle Inspection Based on Template Matching

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICCPR '20: Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition
    October 2020
    552 pages
    ISBN:9781450387835
    DOI:10.1145/3436369
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • Beijing University of Technology

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 11 January 2021

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Template matching
    2. image matching
    3. object location
    4. text location

    Qualifiers

    • Research-article
    • Research
    • Refereed limited

    Conference

    ICCPR 2020

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 27
      Total Downloads
    • Downloads (Last 12 months)1
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 24 Dec 2024

    Other Metrics

    Citations

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media