Dynamic foreground detection based on improved Codebook model

Abstract

Foreground detection method based on improved Codebook algorithm is discussed in this paper: first of all, transform RGB colour space into YCbCr colour space to make chromaticity convergent, and cope with illumination changing. Second, search for the CodeWords matching with the pixel values of the YCbCr to update the algorithm, so as to ensure the foreground detection effect. Then apply random abandon value method to delete the CodeWords that have not been accessed for a long time, reduce memory consumption and improve processing speed. Finally, conduct experiments on the infrared imagery and the colour image, respectively, to make foreground detection. The results demonstrate that the model and algorithm presented in this paper can make better foreground detection and reduce memory consumption. Meanwhile, compare this method with other algorithms to prove its advantages.

Keywords:

• Codebook model
• Foreground detection
• YCbCr
• Infrared imagery
• Random discard value

Disclosure Statement

The authors have declared that no conflict of interest exists.

Acknowledgments

We thank the reviewers for helping us to improve this paper. This work is supported by National Natural Science Foundation of China, No. 61262002, No. 71573122, No. 71303110; China Postdoctoral Science Foundation, No. 2015M580428; Postdoctoral Science Foundation of Jiangsu Province, No. 1402046B; the Fundamental Research Funds for the Central Universities, No. NS2014064.