Vehicle detection algorithm based on codebook and local binary patterns algorithms

被引:4
|
作者
Xu Xue-mei [1 ]
Zhou Li-chao [1 ]
Mo Qin [1 ]
Guo Qiao-yun [1 ]
机构
[1] Cent S Univ, Sch Phys & Elect, Changsha 410083, Peoples R China
基金
中国国家自然科学基金;
关键词
background modeling; Gaussian pyramid; Codebook; Local binary patterns (LBP); moving vehicle detection; SEGMENTATION; SUBTRACTION;
D O I
10.1007/s11771-015-2560-4
中图分类号
TF [冶金工业];
学科分类号
0806 ;
摘要
Detecting the moving vehicles in jittering traffic scenes is a very difficult problem because of the complex environment. Only by the color features of the pixel or only by the texture features of image cannot establish a suitable background model for the moving vehicles. In order to solve this problem, the Gaussian pyramid layered algorithm is proposed, combining with the advantages of the Codebook algorithm and the Local binary patterns (LBP) algorithm. Firstly, the image pyramid is established to eliminate the noises generated by the camera shake. Then, codebook model and LBP model are constructed on the low-resolution level and the high-resolution level of Gaussian pyramid, respectively. At last, the final test results are obtained through a set of operations according to the spatial relations of pixels. The experimental results show that this algorithm can not only eliminate the noises effectively, but also save the calculating time with high detection sensitivity and high detection accuracy.
引用
收藏
页码:593 / 600
页数:8
相关论文
共 50 条
  • [1] Vehicle detection algorithm based on codebook and local binary patterns algorithms
    许雪梅
    周立超
    墨芹
    郭巧云
    [J]. Journal of Central South University, 2015, 22 (02) : 593 - 600
  • [2] Vehicle detection algorithm based on codebook and local binary patterns algorithms
    Xue-mei Xu
    Li-chao Zhou
    Qin Mo
    Qiao-yun Guo
    [J]. Journal of Central South University, 2015, 22 : 593 - 600
  • [3] Smoke vehicle detection based on robust codebook model and robust volume local binary count patterns
    Tao, Huanjie
    Lu, Xiaobo
    [J]. IMAGE AND VISION COMPUTING, 2019, 86 : 17 - 27
  • [4] Face Detection Based on Probability of Amplitude Distribution of Local Binary Patterns Algorithm
    Alobaidi, Wisam H.
    Aziz, Israa T.
    Jawad, Thakwan
    Flaih, Firas M. F.
    Azeez, Abdulrahman T.
    [J]. 2018 6TH INTERNATIONAL SYMPOSIUM ON DIGITAL FORENSIC AND SECURITY (ISDFS), 2018, : 28 - 32
  • [5] Segmentation of moving foreground objects using codebook and local binary patterns
    Li, Bo
    Tang, Zhen
    Yuan, Baozong
    Miao, Zhenjiang
    [J]. CISP 2008: FIRST INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOL 4, PROCEEDINGS, 2008, : 239 - 243
  • [6] A novel sea-land segmentation algorithm based on local binary patterns for ship detection
    Xia, Yu
    Wan, Shouhong
    Jin, Peiquan
    Yue, Lihua
    [J]. 1600, Science and Engineering Research Support Society (07): : 237 - 246
  • [7] Face Liveness Detection Based on Enhanced Local Binary Patterns
    Liu, Xiaolei
    Lu, Runge
    Liu, Wei
    [J]. 2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 6301 - 6305
  • [8] Embedded Face Detection Application based on Local Binary Patterns
    Acasandrei, Laurentiu
    Barriga, Angel
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS, 2014 IEEE 6TH INTL SYMP ON CYBERSPACE SAFETY AND SECURITY, 2014 IEEE 11TH INTL CONF ON EMBEDDED SOFTWARE AND SYST (HPCC,CSS,ICESS), 2014, : 641 - 644
  • [9] Glaucoma Detection based on Local Binary Patterns in Fundus Photographs
    Ali, Maya Alsheh
    Hurtut, Thomas
    Faucon, Timothee
    Cheriet, Farida
    [J]. MEDICAL IMAGING 2014: COMPUTER-AIDED DIAGNOSIS, 2014, 9035
  • [10] Fabric Defect Detection Based on Adaptive Local Binary Patterns
    Fu, Rong
    Shi, Meihong
    Wei, Hongli
    Chen, Huijuan
    [J]. 2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO 2009), VOLS 1-4, 2009, : 1336 - +