【摘要】 视频图像的背景减除是实现运动目标检测与跟踪的关键。由于视频图像种类多且背景复杂多变,没有一种背景减除方法适用于所有复杂或运动背景的视频图像的目标检测。本文基于图像一维最大熵实现复杂及运动背景视频图像的运动目标检测,将目标与背景信息熵最大的灰度值作为目标检测阈值,尽量多地保留运动目标信息。与帧差法、高斯混合建模方法相比发现,一维最大熵方法运算速度快,获得的目标信息完整准确,适用于复杂背景和运动背景的视频图像目标的实时检测。更多还原

【Abstract】 Background subtraction of video image is critical for detecting and tracking moving objects.Because of variety of video image and complicated background,it is difficult for a method to detect moving objects for all video images.This paper proposes the 1-D maximum entropy of image to accomplish the object detection of video images with dynamical and complicated background.The algorithm obtains the gray value which makes the entropy of object and background maximum,retains most information of moving object.Compared with frame difference method and Gaussian mixture background modeling method,1-D maximum entropy method obtains the accurate object with shorter computational time,and much information of object.It is suitable for detecting objects of the videos with dynamical and variable background in real time.更多还原