Motion objects detection in outdoor video surveillance is prone to be disturbed by insignificant motions

such as branches swing and wave

and has low accuracy and bad real-time. So a Region of Interest(ROI) automatic extraction algorithm is proposed in this paper

and ROI has the existing and potential significant motion objects. The algorithm constructs the belt-shaped operators to detect the region existing motion objects

and realizes region growing based on color similarity and region degeneration based on disturbance objects

and then gets the potential significant motion region. Adopting the different detection strategies for different regions can improve the accuracy in real-time. Experimental results show that the algorithm is efficient in extracting ROI. In motion objects detection application

the approach can overcome the influence of insignificant motions

improve the accuracy

and reduce the computation complexity greatly.