Vehicle detection algorithm based on codebook and local binary patterns algorithms
来源期刊：中南大学学报(英文版)2015年第2期
论文作者：XU Xue-mei(许雪梅) ZHOU Li-chao(周立超) MO Qin(墨芹) GUO Qiao-yun(郭巧云)
文章页码：593 - 600
Key words：background modeling; Gaussian pyramid; Codebook; Local binary patterns (LBP); moving vehicle detection
Abstract: 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.
XU Xue-mei(许雪梅), ZHOU Li-chao(周立超), MO Qin(墨芹), GUO Qiao-yun(郭巧云)
(School of Physics and Electronics, Central South University, Changsha 410083, China)
Abstract: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.
Key words:background modeling; Gaussian pyramid; Codebook; Local binary patterns (LBP); moving vehicle detection
