People counting system based on improved Gaussian background model

This paper introduces a novel method to count people which is applied to the ATM surveillance video. In this system, we chose an image without foreground target as the background image. To reduce the interference, updating the background in real-time is a must, and the foreground image is got by the improved Gaussian background difference between current image and background image, then binarizing and morphology processing. After dilating and eroding, the contours of people are clearly presented. We take the contour as a person if the number of the pixels in the contour is more than a certain threshold, and the number of the contours is the number of people. In the end, we utilize the ratio of width to height of the contours to improve the accuracy.