MOVING OBJECT DETECTION USING BACKGROUND SUBTRACTION TECHNIQUES

Now a day, Moving Object detection is becoming very popular, yet challenging vision task. Background subtraction is widely used for extracting unusual motion of object of interest in video images. The proposed algorithms have been used to identify moving objects from the sequence of video frames which contains dynamically changing backgrounds in the noisy atmosphere. There are many challenges in achieving a robust background subtraction algorithm in the external noisy environment. Background subtraction approach is used to separate the moving objects from the background. Many different methods have been proposed over the recent years. In this research work, three different methods studied and implemented by use of simple background subtraction algorithms. Different methods for detecting moving objects are worked out such as: Frame differencing, Mixture of Gaussian and Approximation median filter. It is clearly shown that frame difference method is very simple to understand and implement. It does the best job of subtracting out extraneous background noise but it is not suitable for complex applications. The second method, approximate median, gives us significantly increased accuracy with not much more computation. It had a little trouble with quickly changing light levels, but handled them better than mixture of Gaussians. And Mixture of Gaussians, the most complex of the methods, gives us good performance and reduce the problem of noise that have been studied in previous research