Moving Edge Segment Matching for the Detection of Moving Object

We propose a segment based moving edge detection algorithm by building association from multi-frames of the scene. A statistical background model is used to segregate the moving segments that utilize shape and position information. Edge specific knowledge depending upon background environment is computed and thresholds are determined automatically. Statistical background model gives flexibility for matching background edges. Building association within the moving segments of multi-frame enhances the detection procedure by suppressing noisy detection of flickering segments that occurs frequently due to noise, illumination variation and reflectance in the scene. The representation of edge as edge segment allows us to incorporate this knowledge about the background environment. Experiments with noisy images under varying illumination changing situation demonstrates the robustness of the proposed method in comparison with existing edge pixel based moving object detection methods.