一种古建墙壁受污文字图像的多特征引导Grab Cut分割方法  

Segmentation,an algorithm guided by multiple features to group obscured character images of ancient wall inscriptions

作　　者：刘英杰[1] 杨风暴[1] 吉琳娜[1] 原惠峰 

机构地区：[1]中北大学信息与通信工程学院,山西太原030051

出　　处：《文物保护与考古科学》2017年第6期118-122,共5页Sciences of Conservation and Archaeology

基　　金：山西省自然科学基金资助项目(2013011017-4)

摘　　要：古建墙壁题记毛笔文字受霉变污染影响,字迹不清,不利于辨识,而传统算法对文字图像进行分割时未充分考虑污染和文字的特征信息,结果中往往存在误分割或缺损现象。本研究提出一种结合图像偏振信息的多特征引导Grab Cut分割算法,该方法首先对采集的0°、45°、90°、135°四个角度偏振图像进行斯托克斯解算,得到偏振度特征图;然后利用SLIC对可见光相机采集的题记图像进行超像素分割,并提取超像素的颜色特征距和纹理特征距;最后,用偏振度约束区域项,特征距引导边界项,进行Grab Cut分割,得到毛笔文字分割结果。实验结果表明,本算法与未考虑偏振和特征距信息的图割算法相比,分割效果得到较大改善。研究结果可为书法研究和文字拓本的数字化存储提供有力的科学支持,也为题记的实体去污修复过程提供充足的科学指引和实验环境。Mildew-obscured brush inscriptions on ancient architectural objects are often illegible and not easy to decipher. The traditional character image segmentation algorithm does not take full account of pollution and character feature information,and can lead to incorrect interpretations. This paper presents a multi-feature-guided ＂Grab Cut＂segmentation algorithm used in combination with image polarization information. First,stokes solver was applied to the polarized images at four different angles（ 0°,45°,90° and 135°） to obtain the feature graphs of the degree of polarization. Then SLIC was used to make super pixel division of images of the inscriptions captured by a visible light camera,thus making it possible to extract super pixel feature distances of color and texture. Finally,＂Grab Cut＂segmentation was performed according to regional items（ restrained by the degrees of polarization） and feature distances（ guided by boundary items） to get segmentation results for the characters. Compared with other segmentation algorithms,which do not take into account degrees of polarization or feature distances,this method gave greatly improved segmentation.

关 键 词：毛笔文字 多特征引导 超像素分割 GRAB Cut分割 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]