基于Canny优化的卡通视频分割与矢量化

矢量化的视频图像相对于光栅化的视频图像具有储存容量小、缩放不失真等诸多优点。相对于真实视频,卡通视频因色块明显、线条清晰等特点更适合于进行矢量化处理。基于卡通的特性提出了一种基于Canny边缘检测的优化分割算法。主要针对Canny边缘提取不封闭的特点进行优化,并将其用于图像分割。提出了一种算法来提取卡通动画的素材,并为卡通动画构建素材库。通过素材重用的方式大大地缩小了卡通视频的储存空间,并且很好地解决了卡通视频矢量化问题中极易产生的帧间不一致的问题。实现了一个全自动地进行卡通视频矢量化的系统,其中包括卡通视频的镜头分割、素材库的构建等过程。该系统能够适应多种卡通视频,并能对视频中的细节区域产生较好的效果。

Cartoon Animations Segmentation and Vectorization Based on Canny Optimization

Vectorization of image/video has many potential advantages comparing to a raster format,such as higher compression ratios for storage and allowing display on devices with differing capabilities.Cartoon animations are more suitable for vectorizing than the videos from real world because of their clear edge and region.We proposed a new algorithm of image segmentation based on Canny operator,solved the problem of discontinuity of edge detection and created a material box for each cartoon animation.We proposed a way to low the compression ratio by reusing the material of cartoon in the material box,and also solved the problem of flicker during the vectorization with the material box.We made a system to automaticly vectorize the cartoon animations including the shot segmentation,active region extraction and creating the material box.Our system can give good result on different kinds of cartoon,even those with complex texture in it.