基于计算机视觉的视频图像关键帧提取及修复方法

Key Frame Extraction and Restoration of Video Image Based on Computer Vision

为了提高视频图像关键帧提取及修复效果,设计了一种基于计算机视觉的视频图像关键帧提取及修复方法。基于计算机视觉进行视频图像采集;采用阈值分割法建立灰度值模型,计算背景与目标的灰度差;利用视频图像中的主要特征窗口获取像素值,使用熵值法采集剩余的局部纹理图像,以完成视频图像关键帧提取。在此基础上,利用加权法还原原始矩阵,完成视频图像关键帧修复。实验结果表明,此方法提取的图像清晰度较高,能够提取到图像的颜色特征和纹理特征,提取多个视频图像关键帧的时间较少。

In order to improve the effect of video image key frame extraction and repair,a video image key frame extraction and repair method based on computer vision is designed.The computer vision method is used to collect image information,and the threshold segmentation method is used to establish the gray value model to calculate the gray difference between the background and the target.The main feature window in the video image is used to obtain the pixel value,and the entropy method is used to collect the remaining local texture image to complete the extraction of key frames in the video image.On this basis,the original matrix is restored by weighting method to achieve video image restoration.Experimental results show that this method can extract color features and texture features of the image,and it takes less time to extract key frames of multiple video images.