基于背景减除法的视频序列运动目标检测

视频序列中运动目标的检测是目标识别、标记和追踪的重要组成部分，背景减除法是运动目标检测中被广泛应用的算法。针对光线变化、噪声和局部运动等影响运动目标检测效果的问题，提出一种基于背景减除法的视频序列运动目标检测算法。该算法结合背景减除法和帧间差分法，对当前帧像素点的运动状态进行判断，分别对静止和运动的像素点进行替换和更新，采用最大类间方差（Otsu）法对差分图像进行目标提取，并使用数学形态学运算去除目标中的噪声和冗余信息。实验结果表明，所提算法对于视频序列中运动目标的检测具有较好的视觉效果和较高的准确度，能够克服局部运动以及噪声等缺陷。

Moving object detection based on background subtraction for video sequence

Moving object detection is the essential process of object recognition, marking and tracking in video sequences, the background subtraction algorithm is widely used in moving object detection. Concerning the problem that illumination changing, noise and local motion seriously affect the accuracy of moving object detection, a moving object detection algorithm based on background subtraction for video sequences was proposed. The background subtraction was combined with inter-frame difference to estimate the motion state of current frame pixels. The related pixels in the static and motion region were replaced and updated respectively. The Otsu method was used to extract moving object and the mathematical morphological operation was used to eliminate the noise and redundant information in the objects. The experimental results show that the proposed algorithm has good visual effect and high accuracy for detecting moving objects in video sequences, and it can overcome the shortcomings such as local movement and noise.