Adaptive degraded document image binarization

This paper presents a new adaptive approach for the binarization and enhancement of degraded documents. The proposed method does not require any parameter tuning by the user and can deal with degradations which occur due to shadows, non-uniform illumination, low contrast, large signal-dependent noise, smear and strain. We follow several distinct steps: a pre-processing procedure using a low-pass Wiener filter, a rough estimation of foreground regions, a background surface calculation by interpolating neighboring background intensities, a thresholding by combining the calculated background surface with the original image while incorporating image up-sampling and finally a post-processing step in order to improve the quality of text regions and preserve stroke connectivity. After extensive experiments, our method demonstrated superior performance against four (4) well-known techniques on numerous degraded document images.     

基于视窗的OCR页面图像倾斜检测方法

文档在扫描输入过程中，所生成的页面图像一般都存在一定的角度倾斜，当页面图像倾斜角度过大时，将对进一步的版面分析以及字符识别产生不良影响。为了快速准确地检测页面图像倾斜角度和降低计算量，提出了一种基于视窗变换的页面图像倾斜检测方法，该算法首先对视窗中的文字及图片的细节部分进行模糊，然后对其边沿进行直线拟合，以便快速检测页面图像倾斜角度。实验结果表明，该方法能快速准确地检测出各类页面图像的倾斜角度，并具有良好的适应性。     

结合高阶微分的非局部均值图像去噪算法

非局部均值算法是近年来去噪效果优秀并且引起广泛研究的算法, 但是该算法对于弱纹理, 弱边缘不能很好地保持。在非局部均值算法的基础上, 利用高阶微分可以很好地反映图像的弱边界和振荡等特征的特点, 改进了非局部均值算法。改进的算法能够在去噪的同时保留更多的细节、纹理和弱边缘。     

Extraction of Binary Character/Graphics Images from Grayscale Document Images

The extraction of binary character/graphics images from gray-scale document images with background pictures, shadows, highlight, smear, and smudge is a common critical image processing operation, particularly for document image analysis, optical character recognition, check image processing, image transmission, and videoconferencing. After a brief review of previous work with emphasis on five published extraction techniques, viz., a global thresholding technique, YDH technique, a nonlinear adaptive technique, an integrated function technique, and a local contrast technique, this paper presents two new extraction techniques: a logical level technique and a mask-based subtraction technique. With experiments on images of a typical check and a poor-quality text document, this paper systematically evaluates and analyses both new and published techniques with respect to six aspects, viz., speed, memory requirement, stroke width restriction, parameter number, parameter setting, and human subjective evaluation of result images. Experiments and evaluations have shown that one new technique is superior to the rest, suggesting its suitability for high-speed low-cost applications.     

基于矢量扩散控制的图像同步去噪增强方法

在图像获取过程中,常得到含有噪声和对比度较差的图像,为更好地去除图像的噪声与增强对比度,提出一种基于矢量扩散控制的图像同步去噪增强方法。分析全变分(TV)模型的构造,指出其存在的问题,通过引入矢量扩散控制的方式改造该模型的后项,更好地控制扩散在图像边缘处的粒度。给出限制对比度自适应直方图均衡的微分模型结构,并与改进后的TV模型融合实现图像的同步去噪与反差增强。通过2组实验从成像质量和灰度分布上比较处理结果,验证该方法的有效性。实验结果表明,该方法不仅较好地解决了TV模型在去噪过程中出现的阶梯效应,而且能够改善图像对比度,提高图像的质量。     

雾景降质图像增强算法研究

在对目前雾景降质图像增强文献进行分析与理解的基础上,简单介绍最近十年雾景降质图像增强的研究现状,根据相关文献简要分析了传统雾景降质图像增强方法的缺陷及改进;介绍和评价了几种基于物理模型的天气退化图像复原方法;最后简要对雾景降质图像增强的发展与亟待解决的问题进行了分析与展望。     

动态背景的序列图像中运动小目标检测算法

提出了一种动态背景下红外运动小目标的检测算法。该算法在连续四帧图像配准的基础上,对配准之后的图像序列进行沿时间轴的一维小波变换,实现目标和背景的分离。然后对主要包含运动目标信息的图像按像素相乘的方法得到目标增强图像,对其分割后提取运动小目标。实验结果表明,该方法能够有效的对红外慢速和快速运动的小目标进行检测。     

Automatic accurate broken character restoration for patrimonial documents

In this article, we are interested in the restoration of character shapes in antique document images. This particular class of documents generally present a lot of involuntary historical information that have to be taken into account to get quality digital libraries. Actually, many document processing methods of all sorts have already been proposed to cope with degraded character images, but those techniques often consist in replacing the degraded shapes by a corresponding prototype which is not satisfying for lots of specialists. For that, we decided to develop our own method for accurate character restoration, basing our study on generic image processing tools (namely: Gabor filtering and the active contours model) completed with some specific automatically extracted structural information. The principle of our method is to make an active contour recover the lost information using an external energy term based on the use of an automatically built and selected reference character image. Results are presented for real case examples taken from printed and handwritten documents.     

文本图像的双边总变分超分辨率恢复方法

超分辨率图像复原的目的是从几幅包含有相同观测区域的图像序列中重建更高分辨率的图像。一般的超分辨率算法没有考虑文本图像的分段连续性,因此有可能丢失笔画边缘处的细节信息。双边总变分正则算法具有很好的边缘保持能力,因此可以应用到文本图像的超分辨率恢复。本文根据汉字的字符结构特点,对双边总变分正则算法进行了改进,根据汉字的笔画组成特征。提出新的正则项。该方法由于充分地考虑了汉字文本图像的结构特征,因此能够很好地保持汉字的笔画的尖锐边缘。实验也证明了使用本文所提出的BTVCH算法获得的超分辨率文本图像可以获得最高的字符识别率。     

基于可变模板的文本倾斜检测

在对文本扫描输入的过程中，文本图像不可避免地会发生倾斜，倾斜校正将为图文分割、文字识别等后续处理工作创造良好的条件。基于可变模板技术，提出一种新的倾斜检测方法。在构造表征扫描文本的可变模板和定义合适的能量函数的基础上，采用遗传算法进行快速优化搜索。实验结果表明，该方法能够精确检测文本的倾斜角度，并且不受倾角大小和文字方向的影响，具有较强的抗噪声性和较快的收敛速度。     

Structural feature-based evaluation method of binarization techniques for word retrieval in the degraded Arabic document images

One of the most important and necessary steps in the process of document analysis and recognition is the binarization, which allows extracting the foreground from the background. Several binarization techniques have been proposed in the literature, but none of them was reliable for all image types. This makes the selection of one method to apply in a given application very difficult. Thus, performance evaluation of binarization algorithms becomes therefore vital. In this paper, we are interested in the evaluation of binarization techniques for the purpose of retrieving words from the images of degraded Arabic documents. A new evaluation methodology is proposed. The proposed evaluation methodology is based on the comparison of the visual features extracted from the binarized document images with ground truth features instead of comparing images between themselves. The most appropriate thresholding method for each image is the one for which the visual features of the identified words in the image are “closer” to the features of the reference words. The proposed technique was used here to assess the performances of eleven algorithms based on different approaches on a collection of real and synthetic images.     

自适应的有效非局部图像滤波

研究了基于预选择的非局部均值滤波方法,并指出已有方法在提取图像子块特征方面的不足,利用梯度域奇异值分解(SVD) 提出一种自适应的有效非局部滤波方法。该方法对基于预选择的非局部滤波方法的贡献主要有:1)是一种基于图像子块结构特征的鲁棒预选择方法;2)研究了相似集大小与滤波性能的关系;3)相似子块的自动选取;4)提出一种局部自适应的滤波参数选取方法,根据图像局部内容的不同确定滤波参数。此外,利用欧氏距离的对称性进一步提高运行速度。实验结果表明:本文方法滤波后的图像在主客观方面都优于原算法和其他快速方法,且运行速度较快,是一种有效的滤波方法。     

Document image binarization using background estimation and stroke edges

Document images often suffer from different types of degradation that renders the document image binarization a challenging task. This paper presents a document image binarization technique that segments the text from badly degraded document images accurately. The proposed technique is based on the observations that the text documents usually have a document background of the uniform color and texture and the document text within it has a different intensity level compared with the surrounding document background. Given a document image, the proposed technique first estimates a document background surface through an iterative polynomial smoothing procedure. Different types of document degradation are then compensated by using the estimated document background surface. The text stroke edge is further detected from the compensated document image by using L1-norm image gradient. Finally, the document text is segmented by a local threshold that is estimated based on the detected text stroke edges. The proposed technique was submitted to the recent document image binarization contest (DIBCO) held under the framework of ICDAR 2009 and has achieved the top performance among 43 algorithms that are submitted from 35 international research groups.     

A collaborative enhancement-compression approach for historical document images based on PDE-analysis

Historical document images suffer from several kinds of degradation affecting their readability and increase their sizes when digitizing. Indeed, preserving the old document heritage requires an important storage infrastructures, while this space could be significantly reduced if one manages to safeguard these documents without their considerable amount of artifacts which increasing their entropy. We present in this work a new and more advantageous solution for the document image compression technology dedicated to National Archives and Libraries. The aim of this work is to propose a novel historical document compression scheme judiciously combined with a novel automatic enhancement scheme, both based on PDE-Analysis applied in an innovative way, to face this challenging issue without affecting the look and feel of the historical document image. Throughout experiment, the proposal is fairly evaluated on overall DIBCO datasets and some historical documents collected from the web by means of objective measures and perceptual judgment against the most used enhancement algorithms, the most robust compression standards such as JPEG-XR and the most used sequential compression–enhancement combinations techniques to proof the robustness of the proposed collaborative approach against classic sequential approaches.     

基于字符规范化的文档图像水印算法

运用字符规范化和小波变换的知识,提出一种将文档图像分割成字符图像,再对字符图像规范化,然后将随机序列嵌入到小波图像低频系数的水印算法.根据视觉系统纹理掩蔽特性,将不同强度的水印分量嵌入到了不同的小波系数中.由于文档图像分割和规范化本身具有抗几何攻击的特性,故该方法对缩放、小角度旋转有一定的鲁棒性,实验结果表明:该方法在文档图像上比其它方法更具备优越性.     

基于偏振特征的图像增强算法

具有不同导电特性的表面对入射光偏振态的影响不同,同时描述光束偏振态的线偏振度、偏振角和Stokes矢量之间存在互补性和冗余性;在此基础上提出了一种基于偏振特征和能量特征的图像增强算法,该算法对偏振度、偏振角和Stokes图像进行基于能量特征的融合,实现了对图像的增强,同时利用信息熵、清晰度和对比度对结果进行评价;实验表明,该方法在图像增强方面具有优越性.     

基于机器视觉的发动机包覆层表面缺陷检测技术

固体火箭发动机包覆层表面的缺陷检测是保证其使用安全性的重要手段.本文应用机器视觉技术实现发动机包覆层表面缺陷的自动检测.用工业相机采集发动机包覆层表面的图像,结合图像特点,通过多次实验分析,选择中值滤波方法进行滤波,采用图像模式匹配技术将缺陷从图像背景中分割出来,并将以上功能进行整合,设计缺陷自动检测系统.实验结果表明...     

基于二阶总广义变差的欠采样图像重构方法

针对欠采样图像重构的凸优化问题,提出一种基于二阶总广义变差(TGV)范数最小化的算法。利用图像的二阶TGV半范作为正则约束项,自动地平衡一、二阶导数项,使得该算法可以更好地恢复图像边缘,有利于平滑噪声,避免阶梯效应。为了有效地计算该模型,通过正交投影和调整权重阈值对每一步迭代结果进行修正,最终获得更准确的重构结果。实验结果表明,与正交匹配追踪(OMP)模型和全变差(TV)模型比对,该算法重构的图像其峰值信噪比(PSNR)及结构相似度(SSIM)都有明显的提高,重构效果较好。     

Text segmentation using gabor filters for automatic document processing

There is a considerable interest in designing automatic systems that will scan a given paper document and store it on electronic media for easier storage, manipulation, and access. Most documents contain graphics and images in addition to text. Thus, the document image has to be segmented to identify the text regions, so that OCR techniques may be applied only to those regions. In this paper, we present a simple method for document image segmentation in which text regions in a given document image are automatically identified. The proposed segmentation method for document images is based on a multichannel filtering approach to texture segmentation. The text in the document is considered as a textured region. Nontext contents in the document, such as blank spaces, graphics, and pictures, are considered as regions with different textures. Thus, the problem of segmenting document images into text and nontext regions can be posed as a texture segmentation problem. Two-dimensional Gabor filters are used to extract texture features for each of these regions. These filters have been extensively used earlier for a variety of texture segmentation tasks. Here we apply the same filters to the document image segmentation problem. Our segmentation method does not assume any a priori knowledge about the content or font styles of the document, and is shown to work even for skewed images and handwritten text. Results of the proposed segmentation method are presented for several test images which demonstrate the robustness of this technique. This work was supported by the National Science Foundation under NSF grant CDA-88-06599 and by a grant from E. 1. Du Pont De Nemours & Company.