网格运动分析与形态学滤波相结合的视频对象分割

提出了一种基于二维网格运动分析与改进形态学滤波空域自动分割策略相结合的视频对象时空分割算法。该算法首先利用高阶统计方法对视频图像的二维网格表示进行运动分析，快速得到前景对象区域，通过后处理有效获得前景对象运动检测掩膜。然后，用一种结合交变序列重建滤波算法和自适应阈值判别算法的改进分水岭分割策略有效获得前景对象的精确边缘。最后，用区域基时空融合算法将时域分割结果和空域分割结果结合起来提取出边缘精细的视频对象。实验结果表明，本算法综合了多种算法的优点，主客观分割效果理想。

Video object segmentation by 2-D mesh-based motion analysis and morphological filtering

A new temporal-spatial video object segmentation algorithm was proposed. This algorithm was based on 2-D mesh-based motion analysis and an improved spatial automatic segmenting strategy of morphological filtering. Firstly, higher order statistics was used for motion analysis of the 2-D mesh representation. After post-processing, relatively fine motion detection mask was quickly obtained. Then a novel watershed segmenting strategy based on alternating sequential filtering by reconstruction and adaptive threshold was applied to get the accurate boundary of the foreground object. Finally, the video object was effectively extracted by fusing the temporal and spatial segmentation via region-based method. Experimental results indicate that the proposed algorithm assimilates the advantages of 2-D mesh-based algorithms and pixel-based algorithms, and achieves satisfactory subject and object performance.