A Novel Least Square and Image Rotation based Method for Solving the Inclination Problem of License Plate in Its Camera Captured Image

被引:4
作者
Wu, ChangCheng [1 ]
Zhang, Hao [1 ]
Hua, JiaFeng [1 ]
Hua, Sha [1 ]
Zhang, YanYi [1 ]
Lu, XiaoMing [1 ]
Tang, YiChen [1 ]
机构
[1] Minist Publ Secur, Traff Management Res Inst, 88 QianRong RD, Wuxi, Jiangsu, Peoples R China
关键词
inclination; license plate; rotation; least square method; HUMAN ACTIVITY RECOGNITION; FEATURES;
D O I
10.3837/tiis.2019.12.011
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recognizing license plate from its traffic camera captured images is one of the most important aspects in many traffic management systems. Despite many sophisticated license plate recognition related algorithms available online, license plate recognition is still a hot research issue because license plates in each country all round the world lack of uniform format and their camera captured images are often affected by multiple adverse factors, such as low resolution, poor illumination effects, installation problem etc. A novel method is proposed in this paper to solve the inclination problem of license plates in their camera captured images through four parts: Firstly, special edge pixels of license plate are chosen to represent main information of license plates. Secondly, least square methods are used to compute the inclined angle of license plates. Then, coordinate rotation methods are used to rotate the license plate. At last, bilinear interpolation methods are used to improve the performance of license plate rotation. Several experimental results demonstrated that our proposed method can solve the inclination problem about license plate in visual aspect and can improve the recognition rate when used as the image preprocessing method.
引用
收藏
页码:5990 / 6008
页数:19
相关论文
共 23 条
  • [1] Coordinate Rotation Based Low Complexity N-D FastICA Algorithm and Architecture
    Acharyya, Amit
    Maharatna, Koushik
    Al-Hashimi, Bashir M.
    Reeve, Jeff
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2011, 59 (08) : 3997 - 4011
  • [2] License plate recognition from still images and video sequences: A survey
    Anagnostopoulos, Christos-Nikolaos E.
    Anagnostopoulos, Ioannis E.
    Psoroulas, Ioannis D.
    Loumos, Vassili
    Kayafas, Eleftherios
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2008, 9 (03) : 377 - 391
  • [3] [Anonymous], GA36
  • [4] [Anonymous], P IEEE INT C MULT EX
  • [5] [Anonymous], P IEEE INT C IM PROC
  • [6] Strokelets: A Learned Multi-Scale Mid-Level Representation for Scene Text Recognition
    Bai, Xiang
    Yao, Cong
    Liu, Wenyu
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2016, 25 (06) : 2789 - 2802
  • [7] Dense RGB-D Map-Based Human Tracking and Activity Recognition using Skin Joints Features and Self-Organizing Map
    Farooq, Adnan
    Jalal, Ahmad
    Kamal, Shaharyar
    [J]. KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2015, 9 (05): : 1856 - 1869
  • [8] Depth Video-based Human Activity Recognition System Using Translation and Scaling Invariant Features for Life Logging at Smart Home
    Jalal, A.
    Uddin, Md Zia
    Kim, T. -S.
    [J]. IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2012, 58 (03) : 863 - 871
  • [9] Robust human activity recognition from depth video using spatiotemporal multi-fused features
    Jalal, Ahmad
    Kim, Yeon-Ho
    Kim, Yong-Joong
    Kamal, Shaharyar
    Kim, Daijin
    [J]. PATTERN RECOGNITION, 2017, 61 : 295 - 308
  • [10] Shape and Motion Features Approach for Activity Tracking and Recognition from Kinect Video Camera
    Jalal, Ahmad
    Kamal, Shaharyar
    Kim, Daijin
    [J]. 2015 IEEE 29TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS WORKSHOPS WAINA 2015, 2015, : 445 - 450