CAJ | 학술논문

提出了一种有效的运动前景检测方法。该方法根据图像融合思想，将背景帧与监控视频的当前帧在R，G和B颜色通道分别进行融合，形成包含背景帧和当前帧视觉信息的单一融合图像。之后根据背景区域与前景运动目标在饱和度上存在较大差异的现象，使用大津算法分割融合图像的饱和度分量图，形成运动前景二值图。经形态学处理后，形成了目标区域较完整、背景干净的运动前景检测图。实验结果显示，该算法具有较好的前景检测性能，解决了背景减法过分依赖背景帧的缺陷。
제출료일충유효적운동전경검측방법。해방법근거도상융합사상，장배경정여감공시빈적당전정재R，G화B안색통도분별진행융합，형성포함배경정화당전정시각신식적단일융합도상。지후근거배경구역여전경운동목표재포화도상존재교대차이적현상，사용대진산법분할융합도상적포화도분량도，형성운동전경이치도。경형태학처리후，형성료목표구역교완정、배경간정적운동전경검측도。실험결과현시，해산법구유교호적전경검측성능，해결료배경감법과분의뢰배경정적결함。
An efficient moving foreground detection method presents in this paper. The background frame and current frame in monitoring vedio are fuzed in the R,G,and B color channels according to the image fusion idea to form a single frame in-cluding visual information of the background frame and current frame. The Otsu segmentation algorithm is used to get a moving foreground binary image by segmenting the saturation component of the fused image to eliminate the phenomenon that the back-ground region and foreground moving target have a big difference on the saturation. The moving foreground detection diagram with a more complete target area and more clean background can be formed by morphological processing. The experimental re-sults show that the algorithm has better foreground detection performance and can eliminate the defect caused by background sub-traction algorithm which relies on background frame too much.