基于角点运动约束的感兴趣区域提取算法

INTERESTED REGION EXTRACTION ALGORITHM BASED ON CORNER MOVING CONSTRAINTS

传统光流法提取感兴趣区域时运算量巨大,不能满足实时性的要求。针对这一问题提出一种基于角点运动约束的感兴趣区域提取算法。算法利用Harris算法对视频图像进行角点检测,通过对角点区域进行预处理,提取出前景角点区域,在此基础上利用光流法建立角点区域光流场,通过建立运动约束和阈值处理提取运动目标前景。算法仿真结果显示:算法可以准确提取感兴趣区域,抗干扰能力强,可以满足实时性的要求。

Traditional optical flow method can not meet the requirement of real-time property due to huge computation workload when extracting the interested region.In light of this,we propose an algorithm for extracting interested region which is based on corner moving constraints.First,the new algorithm uses Harris algorithm to detect corners on the video image,by pre-processing the corner area to extract the corner area of the foreground.Secondly,on this basis the optical flow method is made use of to establish the optical flow field of corner area,by setting up motion constraint and threshold treatment to extract the foreground of moving target.Experimental results of the algorithm show that the algorithm can accurately extract the interested region,it is strong in anti-jamming and can meet real-time requirement.