一种融合纹理和颜色信息的背景建模方法
PDF下载 (461)王吉文,何加铭.一种融合纹理和颜色信息的背景建模方法[J].宁波大学学报(理工版),2013,26(01):43-47.DOI:
WANG Ji-wen,HE Jia-ming.Background Modeling Algorithm Based on Combination of Texture and Color[J].Journal of Ningbo University(Natural Science & Engineering Edition),2013,26(01):43-47.DOI:
| Title: | Background Modeling Algorithm Based on Combination of Texture and Color |
| 作者: | 王吉文, 何加铭 |
| Author(s): | WANG Ji-wen, HE Jia-ming |
| 关键词: | 运动目标检测; 背景差分; 背景建模; 纹理信息; 局部二值模式; 抗噪因子 |
| Keywords: | moving objects detection; background subtraction; background model; texture information; local binary pattern; anti-noise factor |
| 分类号: | TP391.4 |
| 文献标识码: | A |
| 摘要: | 鉴于目前视频序列的运动目标检测常使用背景差分法, 但其受光照变化以及阴影影响, 不能准确区分出运动物体的特点, 因此提出一种新的背景建模算法. 该算法融合纹理信息和颜色信息建立背景模型, 其中的纹理信息采用LBP算子进行描述. 为更好地描述纹理信息, 进一步改进了基本的LBP算子, 并同时引入抗噪因子增强抗噪声影响. 实验证明, 提出的算法在大多数情况下都取得良好的效果. |
| Abstract: | Currently, the background subtraction is often used in moving target detection of video sequences. However, with the varying illumination and shadow, this method can not accurately distinguish motioning objects. To tackle this shortfall, a new background modeling algorithm which fuses texture and color information to create a background model is proposed in this paper. The texture information is often described with LBP (local binary pattern, local binary mode) operator. The basic LBP operator is improved in this work to characterize the texture information, while the anti-noise factor is also introduced to enhance the anti-noise impact. Experimental results show that the proposed algorithm has achieved satisfactory results in most cases. |
| 参考文献 /References: | [1] Wren C R, Azarbayejani A, Darrell T, et al. Real-time tracking of the human body[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 1997, 19(7): 780-785. [2] Stauffer C, Grimson W E L. Adaptive background mixture models for real-time tracking[C]. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1999:246-252. [3] Lee D S. Effective Gaussian mixture learning for video background subtraction[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(5): 827-832. [4] Lin H H, Chuang J H, Liu T L. Regularized background adaptation: A novel learning rate control scheme for Gaussian mixture modeling[J]. IEEE Transactions on Image Processing, 2011, 20(3):822-836. [5] Heikkila M, Pietikainen M. A texture-based method for modeling the background and detecting moving objects[J]. IEEE Transactions on Pattern Analysis and Machine Inte- lligence, 2006, 28(4):657-662. [6] Zhang Baochang, Gao Yongsheng. Kernel similarity modeling of texture pattern flow for motion detection in complex background[J]. IEEE Transactions on circuits and systems for video technology, 2011, 21(1):29-38. [7] Kim W, Kim C. Background subtraction for dynamic texture scenes using fuzzy color histograms [J]. IEEE Signal processing letters, 2012, 19(3):127-130. [8] Marks T K, Hershey J R, Movellan J R. Tracking motion, deformation, and texture using conditionally Gaussian processes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(2):348-363. [9] 徐剑, 丁晓青, 王生进, 等. 一种融合局部纹理和颜色信息的背景减除方法[J]. 自动化学报, 2009, 35(9):1145- 1150. [10] Chua T W. Fuzzy rule-based system for dynamic texture and color based background subtraction[C]. 2012 IEEE International Conference on Fuzzy Systems, Brisbane, QLD, 2012:1-7. [11] 刘泉志, 胡福桥. 混合高斯模型和LBP纹理模型相融合的背景建模[J]. 微型电脑应用, 2010, 26(9):42-45. |
| 备注/Memo: | 收稿日期: 2012?10?08. 基金项目: 国家科技重大专项(2011ZX03002-004-02); 浙江省移动网络应用技术联合重点实验室项目(2010E10005).第一作者: 王吉文(1987-), 男, 福建南平人, 在读硕士研究生, 主要研究方向: 系统集成与智能控制. E-mail: boot.bin@163.com. *通信作者: 何加铭(1949-), 男, 浙江杭州人, 博士/教授, 主要研究方向: 系统集成与智能控制. E-mail: hejiaming@nbu.edu.cn 宁波大学学报(理工版)网址:http://journallg.nbu.edu.cn/ |