Foreground-Background Segmentation Based on Codebook and Edge Detector
This is an incremental improvement for video surveillance or computer vision applications.
The paper tackles moving object detection in video by combining a codebook segmentation algorithm with edge detectors, and presents results comparing the detection quality using frame-based metrics.
Background modeling techniques are used for moving object detection in video. Many algorithms exist in the field of object detection with different purposes. In this paper, we propose an improvement of moving object detection based on codebook segmentation. We associate the original codebook algorithm with an edge detection algorithm. Our goal is to prove the efficiency of using an edge detection algorithm with a background modeling algorithm. Throughout our study, we compared the quality of the moving object detection when codebook segmentation algorithm is associated with some standard edge detectors. In each case, we use frame-based metrics for the evaluation of the detection. The different results are presented and analyzed.