CAJ | 학술논문

近年来,研究者们提出了许多算法来处理前景提取和图像抽取问题.然而,这些算法存在许多共同缺点:需要三元图作为输入、计算时间过长、大部分算法仅仅使用颜色信息等等.在这篇文章里,作者提出了一种新的快速多层次前景提取办法.首先,应用一种改进的多层次图分割算法,将输入图像粗略地分割为前景和背景两个部分.然后,使用信念传播算法(belief propagation)估计前景/背景交界处像素的不透明度.不同于通常的信念传播算法,在平滑项和颜色项之外,作者通过构造灰度共生矩阵引人了纹理信息.鉴于数码相机图像的分辨率仍在持续快速增长,作者提出的多层次图分割算法可以在加速上述计算过程的同时,获得可以和当前许多算法相媲美的局部最优解.实验结果证明文中所提出的算法对于大尺寸图像尤其有效.
근년래,연구자문제출료허다산법래처리전경제취화도상추취문제.연이,저사산법존재허다공동결점:수요삼원도작위수입、계산시간과장、대부분산법부부사용안색신식등등.재저편문장리,작자제출료일충신적쾌속다층차전경제취판법.수선,응용일충개진적다층차도분할산법,장수입도상조략지분할위전경화배경량개부분.연후,사용신념전파산법(belief propagation)고계전경/배경교계처상소적불투명도.불동우통상적신념전파산법,재평활항화안색항지외,작자통과구조회도공생구진인인료문리신식.감우수마상궤도상적분변솔잉재지속쾌속증장,작자제출적다층차도분할산법가이재가속상술계산과정적동시,획득가이화당전허다산법상비미적국부최우해.실험결과증명문중소제출적산법대우대척촌도상우기유효.
In recent years researchers have developed many algorithms for object extraction and image matting. However, previous approaches usually require trimaps as input, or consume in-tolerably long time to get the final results, and most of them just consider the color information. This paper proposes a novel fast hierarchical object extraction method. First the input image is segmented roughly into two regions: foreground and background, using a modified hierarchical Graph Cuts algorithm. After that, the opacity values for the pixels nearby the foreground/back-ground border are estimated using belief propagation (BP). Unlike traditional BP-based approa-ches, besides the smoothness and color constraints, the texture information is introduced by building grayscale co-occurrence matrices. Moreover, considering the fact that the resolution of photographs taken by digital cameras continues to increase at a rapid and steady pace, the modi-fied version of hierarchical Graph Cuts proposed in this paper could accelerate the above-men-tioned computation process, getting a comparably satisfactory local optimal solution as previous ap-proaches. Experiments show that the method is effective and efficient especially for large images.