TY  - JOUR
T1  - Segmentation of Moving Objects Using a Mutual- Information Based Combination Scheme
AU - , Yaming Wang AU - , Yunhua Zhang AU - , Li Cao AU - , Weida Zhou AU - , Wenqing Huang 
JO  - Asian Journal of Information Technology
VL  - 4
IS  - 2
SP  - 218
EP  - 222
PY  - 2005
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2005.218.222
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2005.218.222
KW  - 
AB  - To segment the moving objects from image sequence is an important problem in computer vision. In this paper, a novel approach is proposed for moving objects segmentation from grayscale image sequence. In order to increase the robustness of segmentation, the information-theoretic principle of mutual information is proposed to combine two different segmentation results. First, the adaptive Gaussian distribution model for each image pixel is presented. Based on this model, each image frame is mapped from spatial domain to statistic domain. The segmentation is consequently performed in statistic domain. Meanwhile the image frame is segmented using Otsu`s method (Otsu, N., 1979) This two segmentation results are then combined by using mutual information and the final result is obtained. Experimental results from a real image sequence show the feasibility of the proposed approach.
ER  -