Video Frame Extraction Process on Canny Edge Detector

This paper presents a technique for motion detection that incorporates several innovative mechanisms. For example, our proposed technique stores, for each pixel, a set of values taken in th neighborhood. It then compares this set to the current pixel value in order to determine whether that pixel belongs to the background, and adapts the model by choosing randomly which values to substitute from the backg This approach differs from those based upon the classical belief that the oldest values should be replaced first. Finally, when the pixel is found to be part of the background, its value is propagated into the background model of a neighboring pixel. We describe our method in full details (including pseudo and compare it to other background subtraction techniques. Efficiency figures show that our method outperforms recent and proven state-of-the-art methods i In this project, we propose a universal sample detection, which combines three innovative techniques. First, we propose a classification model seco explained how motion detection can be initialized with a single frame. Finally, we presented our last innovation: an original update mechanism