@article {10.3844/jcssp.2012.1077.1084,
article_type = {journal},
title = {Using Multi-Scale Filtering to Initialize a Background Extraction Model},
author = {Davarpanah, S. H. and Khalid, Fatimah and Lili, N. A. and Puteri, S. S. and Golchin, M.},
volume = {8},
number = {7},
year = {2012},
month = {May},
pages = {1077-1084},
doi = {10.3844/jcssp.2012.1077.1084},
url = {https://thescipub.com/abstract/jcssp.2012.1077.1084},
abstract = {Problem statement: Probability-based methods which usually work based on the saved history of each pixel are utilized severally in extracting a background image for moving detection systems. Probability-based methods suffer from a lack of information when the system first begins to work. The model should be initialized using an alternative accurate method. Approach: The use of a nonparametric filtering to calculate the most probable value for each pixel in the initialization phase can be useful. In this study a complete system to extract an adaptable gray scale background image is presented. It is a probability-based system and especially suitable for outdoor applications. The proposed method is initialized using a multi-scale filtering method. Results: The results of the experiments certify that not only the quality of the final extracted background is about 10% more accurate in comparison to four recent re-implemented methods, but also the time consumption of the extraction are acceptable. Conclusion: Using multi-scale filtering to initialize the background model and to extract the background using a probability-based method proposes an accurate and adaptable background extraction method which is able to handle sudden and large illumination changes.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}