Digital Signal Processing Reference
In-Depth Information
(a) (b) (c)
Fig. 3.
"smear"processing (a) Original image, (b) Classic mixture Gauss model, (c) The
proposed algorithm
From figure2 and figure3, we can see that after using our algorithm, it can
effectively eliminate the phenomenon of "ghosting" and "smear".
6
Conclusion
This paper describes the basic mixture Gauss model modeling principle and parameter
updating method. And on this basis, we use the frame difference method thought to
improved mixture Gauss model. It effective solved the "ghosting" when static object
re-sports and "smear" when moving object gradually be stationary into the
background, in some degree weaken the effect to the mixture Gauss model caused by
light mutation.
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