基于图切割的图像分割是近几年发展的一项新技术,但随着图像大小及空间维数的增加,图切割的运算量成为负担。针对运动分割提出了一种快速图切割方法,利用运动分割的特点将差分图像中不变的背景映射为一点或几点,然后参与网络图的构造和图切割的求解,以减少图切割运算量。通过实验将这种快速方法应用于2D图切割和3D图切割,对图像序列的运动目标分别进行了自动分割。实验结果表明,这种快速图切割方法不仅大大地降低了存储消耗,提高了运算速度,而且也获得了良好的分割结果。结果证明这种方法在运动目标的分割中是行之有效的。
Image segmentation based on graph cuts is a newly developing technology in recent years. But the memory overhead and time complexity of leading algorithms result in an excessive computational burden along with the increase in the size of images and spatial dimension. A fast method of motion segmentation based on graph cuts is proposed. To speed up the computation of graph cuts, the background pixels of the difference image are mapped into one or several points to participate in the creating and solving of network graphs. Through the experiments of 2D and 3D graph cuts, the fast method is applied to segment motion objects automatically in 2D image sequence and 3D spatio-temporal volume. The results of experiments show that this method reduces both the running time and the memory consumption of graph cuts while producing nearly the same segmentation result as the general graph cuts. It is showed that the method is fast and effective in motion segmentation.