针对现有镜头检测算法在处理运动信息时无法随着帧间差异不同而变化的问题，提出一种基于光流的镜头边界检测方法。依据光流算法对图像间熵计算进行校正，并提出一种光流量化方法。使用量化值与校正熵值判断图像连续性，保留存在镜头切换的候选边界；根据镜头构造的差异提取图像的光度信息与图像间互信息，并提出一种模型匹配的方式进行镜头类型识别。在互信息提取前对图像进行显著区域提取，来增加图像间的差异而保证模型匹配的准确性。实验表明，该检测算法能准确检测镜头边界且有效排除运动干扰。

To solve the problem that motion information in the video is combined to the detection process of the shot boundary, which is to prevent the impact of target movement, camera movement for detection, a shot boundary detection method based on optical flow is proposed. Firstly, motion information in video using optical flow method was detected, which is used to calculate the entropy of adjacent image correction, and a method of optical flow quantization is proposed. The quantization value and corrected entropy is used to determine the continuity of the image, and candidate boundaries are reserved for the presence of a lens switch. Secondly, the image of the photometric information and mutual information between the images are extracted using the difference between the lens structure, and a model matching method is proposed to identify the type of shot. Significant areas of the image are extracted for computing mutual information, which increases the difference between the images and ensures the accuracy of the model matching. The results show that the algorithm can accurately detect the shot boundary, and effectively eliminate the interference of motion.