CVGIP: Graphical Models and Image Processing最新文献

A New Dynamic Approach for Finding the Contour of Bi-Level Images 一种寻找双水平图像轮廓的动态新方法

CVGIP: Graphical Models and Image Processing Pub Date : 1994-11-01 DOI: 10.1006/cgip.1994.1045

Chow L.R., Liu H.C., Hsu S.Y., Wu D.W.

引用次数: 4

Binarization and Multithresholding of Document Images Using Connectivity 基于连通性的文档图像二值化和多阈值化

CVGIP: Graphical Models and Image Processing Pub Date : 1994-11-01 DOI: 10.1006/cgip.1994.1044

O’Gorman Lawrence

{"title":"Binarization and Multithresholding of Document Images Using Connectivity","authors":"O’Gorman Lawrence","doi":"10.1006/cgip.1994.1044","DOIUrl":"10.1006/cgip.1994.1044","url":null,"abstract":"<div><p>Thresholding is a common image processing operation applied to gray-scale images to obtain binary or multilevel images. Traditionally, one of two approaches is used: global or locally adaptive processing. However, each of these approaches has a disadvantage: the global approach neglects local information, and the locally adaptive approach neglects global information. A thresholding method is described here that is global in approach, but uses a measure of local information, namely connectivity. Thresholds are found at the intensity levels that best preserve the connectivity of regions within the image. Thus, this method has advantages of both global and locally adaptive approaches. This method is applied here to document images. Experimental comparisons against other thresholding methods show that the connectivity-preserving method yields much improved results. On binary images, this method has been shown to improve subsequent OCR recognition rates from about 95% to 97,5%. More importantly, the new method has been shown to reduce the number of binarization failures (where text is so poorly binarized as to be totally unrecognizable by a commercial OCR system) from 33% to 6% on difficult images. For multilevel document images, as well, the results show similar improvement.</p></div>","PeriodicalId":100349,"journal":{"name":"CVGIP: Graphical Models and Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1994-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/cgip.1994.1044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125273606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 164

Novel Deconvolution of Noisy Gaussian Filters with a Modified Hermite Expansion 基于改进Hermite展开的高斯滤波器反卷积算法

CVGIP: Graphical Models and Image Processing Pub Date : 1994-11-01 DOI: 10.1006/cgip.1994.1040

Konstantopoulos C., Hohlfeld R., Sandri G.

引用次数: 1

Estimation of Edge Parameters and Image Blur Using Polynomial Transforms 基于多项式变换的边缘参数估计与图像模糊

CVGIP: Graphical Models and Image Processing Pub Date : 1994-11-01 DOI: 10.1006/cgip.1994.1041

Kayargadde V., Martens J.B.

{"title":"Estimation of Edge Parameters and Image Blur Using Polynomial Transforms","authors":"Kayargadde V., Martens J.B.","doi":"10.1006/cgip.1994.1041","DOIUrl":"10.1006/cgip.1994.1041","url":null,"abstract":"<div><p>A method is presented for detecting blurred edges in images and for estimating the following edge parameters: position, orientation, amplitude, mean value, and edge slope. The method is based on a local image decomposition technique called a polynomial transform. The information that is made explicit by the polynomial transform is well suited to detect image features, such as edges, and to estimate feature parameters. By using the relationship between the polynomial coefficients of a blurred feature and those of the <em>a priori</em> assumed (unblurred) feature in the scene, the parameters of the blurred feature can be estimated. The performance of the proposed edge parameter estimation method in the presence of image noise has been analyzed. An algorithm is presented for estimating the spread of a position-invariant Gaussian blurring kernel, using estimates at different edge locations over the image. First a single-scale algorithm is developed in which one polynomial transform is used. A critical parameter of the single-scale algorithm is the window size, which has to be chosen <em>a priori</em>. Since the reliability of the estimate for the spread of the blurring kernel depends on the ratio of this spread to the window size, it is difficult to choose a window of appropriate size <em>a priori</em>. The problem is overcome by a multiscale blur estimation algorithm where several polynomial transforms at different scales are applied, and the appropriate scale for analysis is chosen <em>a posteriori</em>. By applying the blur estimation algorithm to natural and synthetic images with different amounts of blur and noise, it is shown that the algorithm gives reliable estimates for the spread of the blurring kernel even at low signal-to-noise ratios.</p></div>","PeriodicalId":100349,"journal":{"name":"CVGIP: Graphical Models and Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1994-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/cgip.1994.1041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122298709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 39

Estimating Band-to-Band Misregistrations in Aliased Imagery 混叠图像中带间误配的估计

CVGIP: Graphical Models and Image Processing Pub Date : 1994-11-01 DOI: 10.1006/cgip.1994.1043

Berman M., Bischof L.M., Davies S.J., Green A.A., Craig M.

引用次数: 12

Author Index for Volume 56 第56卷作者索引

CVGIP: Graphical Models and Image Processing Pub Date : 1994-11-01 DOI: 10.1006/cgip.1994.1047

引用次数: 0

1993–1994 Reviewer Acknowledgment 1993-1994年审稿人致谢

CVGIP: Graphical Models and Image Processing Pub Date : 1994-11-01 DOI: 10.1006/cgip.1994.1046

引用次数: 0

Building Skeleton Models via 3-D Medial Surface Axis Thinning Algorithms 通过三维内表面轴细化算法构建骨架模型

CVGIP: Graphical Models and Image Processing Pub Date : 1994-11-01 DOI: 10.1006/cgip.1994.1042

Lee T.C., Kashyap R.L., Chu C.N.

引用次数: 1376

A New Approach for Multilevel Threshold Selection 一种多层阈值选择的新方法

CVGIP: Graphical Models and Image Processing Pub Date : 1994-09-01 DOI: 10.1006/cgip.1994.1033

Papamarkos N., Gatos B.

引用次数: 120

Utilization of Information Measure as a Means of Image Thresholding 利用信息度量作为图像阈值分割的手段

CVGIP: Graphical Models and Image Processing Pub Date : 1994-09-01 DOI: 10.1006/cgip.1994.1037

Shanbhag A.G.

引用次数: 224