一种改进的One-Cut交互式图像分割算法

An improved One-Cut interactive image segmentation algorithm

GrabCut算法作为一种典型的交互式彩色图像分割算法,是计算机图像领域中的重要技术手段。然而随着大数据时代的到来,图像数据种类和数量都呈指数级增长,显著地增加了图像分割的任务量,对图像分割效率提出了更高的要求。针对GrabCut算法图像分割效率及精度低的问题,提出了一种改进的One-Cut交互式图像分割算法。首先采用One-Cut的L_1距离项构建能量函数避免GrabCut算法所面临的NP-hard问题。然后改进能量函数中表观重叠惩罚项,并结合颜色直方图加速技术,优化网络图结构,显著降低网络图的复杂度,从而提高图像分割的效率及精度。实验结果表明,改进后的One-Cut图像分割算法显著提升了图像分割效率,提高了分割精度,得到了较好分割结果。

As a typical interactive color image segmentation method,the Grabcut algorithm is an important technique in the field of computer image.However,with the arrival of big data age,the types and quantities of image data are increasing exponentially.The workload of image segmentation is significantly increasing,and a higher demand is raised for the efficiency of image segmentation algorithms.Aiming at the problem of low efficiency and accuracy of the GrabCut algorithm,we propose an improved One-Cut interactive image segmentation algorithm.Firstly,the energy function is built with the OneCut L1 distance term to avoid the Np-hard problem faced by the GrabCut algorithm.Secondly,the apparent overlap penalty in the energy function is improved and the network structure is optimized by the color histogram acceleration technique.Finally,the complexity of the network diagram is reduced and the image segmentation efficiency and accuracy are improved.Experimental results show that the improved One-Cut interactive image segmentation algorithm can significantly improve the segmentation efficiency and segmentation accuracy and a better segmentation result is obtained.