Affiliation:
1. University of Tunis El Manar, Tunisia
Abstract
Moving object detection is a fundamental task on smart CCTV systems, as it provides a focal point for further investigation. In this study, an algorithm for moving object detection in video, which is thresholded using a stationary wavelet transform (SWT), is developed. In the detection steps, the authors perform a background subtraction algorithm; the obtained results are decomposed using discrete stationary wavelet transform 2D, and the coefficients are thresholded using Birge-Massart strategy. This leads to an efficient calculation method and system compared to existing traffic estimation methods.
Reference17 articles.
1. Complex wavelet based moving object segmentation using approximate median filter-based method for video surveillance.;K.Alok;International Advance Computing Conference (IACC),2014
2. A Comparison of Some Thresholding Selection Methods for Wavelet Regression.;M.Alsaidi;International Journal of Mathematics and Computer Science,2010
3. Nonlinear wavelet image processing: variational problems, compression, and noise removal through wavelet shrinkage
4. Efficient modified directional lifting-based discrete wavelet transform for moving object detection;Chih-Hsien;Signal Processing,2014
5. De-noising by soft-thresholding