基于颜色和纹理信息的快速前景提取方法.docVIP

基于颜色和纹理信息的快速前景提取方法 穆亚东, 周秉锋 北京大学计算机科学技术研究所, 中国北京，100871 摘 要: 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，我们提出了一种新的快速多层次前景提取方法。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，我们通过构造灰度共生矩阵引入了纹理信息。鉴于数码相机图像的分辨率仍在持续快速增长，我们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。实验结果证明本文所提出的算法对于大尺寸图像尤其有效。 关键词: 分层图分割，信念传播，共生矩阵，马尔科夫随机场 中图法分类号：TP391 A Fast Object Extraction Method Based on Color and Texture Information MU Yadong, ZHOU Bingfeng Institute of Computer Science and Technology, Peking University, Beijing 100871, China Abstract: In recent years researchers have developed many algorithms for object extraction and image matting. However, previous approaches usually require trimaps as input, or consume intolerably long time to get the final results, and most of them just consider the color information. In this paper we proposed a novel fast hierarchical object extraction method. First we segment the input image roughly into two regions: foreground and background, using a modified hierarchical Graph Cuts algorithm. After that, we estimate the opacity values for the pixels nearby the foreground/background border using belief propagation (BP). Unlike traditional BP-based approaches, besides the smoothness and color constraints, we also introduce the texture information 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 modified version of hierarchical Graph Cuts which we propose could accelerate the above-mentioned computation process, getting a comparably satisfactory local optimal solution as previous approaches. Experiments show that our method is effective and efficient especially for large images. Key words: hierarchical graph cuts, belief propagation (BP), co-occurrence matrix, Markov Ransom Fields 引言 图像抽取技术在个人相片编辑、影视制作、广告设计、相片