BACKGROUND EXTRACTION METHOD USING THE SECOND DERIVATIVE FILTER IN THE GRADIENT DIRECTION
The paper proposes a new approach to improve traditional background extraction algorithms by integrating a boundary detector with a second derivative filter in the gradient direction. The four main methods of background extraction, namely the inter-frame difference method, the approximate median method, the moving average method and the Gaussian moving average method determine pixels at the boundaries of foreground objects rather unsatisfactorily. The pixel intensity is less than the specified threshold value, and the size of the resulting binary object is smaller when extracted. Therefore, to improve the detection of borders after applying these methods of background extraction, as well as to restore the missing pixels, the filter proposed above is introduced. The results showed that combining the second derivative filter in the gradient direction with each elementary method improves the performance of object segmentation. This was confirmed by the analysis of the average percentage of accuracy. Thus, it was concluded that the new hybrid method of background extraction significantly improves the existing methods of background extraction.