A practical several moving objects area extraction using a half-cosine function wavelet network

This paper describes a practical several moving objects area extraction using a half-cosine function wavelet network. The network decomposes an image into weighted basis functions corresponding to spatial frequency. In this method, objects are distinguished by using a difference of object´s size. First, moving objects area can be extracted from the weight image of the basis functions which constructs the reconstructed image by using frame difference. After that objects with different size are distinguished by using level-image difference. The proposed method enables measurement and area extraction of objects simultaneously. Moving objects area extraction from an image stream which includes several different-size objects is investigated. We show that the proposed basis function based method has robustness against background noise.