Segmentation of Page Images Using the Area Voronoi Diagram
01 Jun 1998-Computer Vision and Image Understanding (Elsevier Science Inc.)-Vol. 70, Iss: 3, pp 370-382
TL;DR: It is confirmed that the proposed method of page segmentation based on the approximated area Voronoi diagram is effective for extraction of body text regions, and it is as efficient as other methods based on connected component analysis.
About: This article is published in Computer Vision and Image Understanding.The article was published on 1998-06-01. It has received 289 citations till now. The article focuses on the topics: Voronoi diagram & Connected-component labeling.
Citations
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13 Jan 2003
TL;DR: This paper provides a detailed survey of past work on document structure analysis algorithms and summarize the limitations of past approaches.
Abstract: Document structure analysis can be regarded as a syntactic analysis problem. The order and containment relations among the physical or logical components of a document page can be described by an ordered tree structure and can be modeled by a tree grammar which describes the page at the component level in terms of regions or blocks. This paper provides a detailed survey of past work on document structure analysis algorithms and summarize the limitations of past approaches. In particular, we survey past work on document physical layout representations and algorithms, document logical structure representations and algorithms, and performance evaluation of document structure analysis algorithms. In the last section, we summarize this work and point out its limitations.
278 citations
27 Jan 2008
TL;DR: The current status of the OCR system, its general architecture, as well as the major algorithms currently being used for layout analysis and text line recognition are described.
Abstract: OCRopus is a new, open source OCR system emphasizing modularity, easy extensibility, and reuse, aimed at both the research community and large scale commercial document conversions. This paper describes the current status of the system, its general architecture, as well as the major algorithms currently being used for layout analysis and text line recognition.
239 citations
TL;DR: A vectorial score that is sensitive to, and identifies, the most important classes of segmentation errors (over, under, and mis-segmentation) and what page components (lines, blocks, etc.) are affected.
Abstract: Informative benchmarks are crucial for optimizing the page segmentation step of an OCR system, frequently the performance limiting step for overall OCR system performance. We show that current evaluation scores are insufficient for diagnosing specific errors in page segmentation and fail to identify some classes of serious segmentation errors altogether. This paper introduces a vectorial score that is sensitive to, and identifies, the most important classes of segmentation errors (over, under, and mis-segmentation) and what page components (lines, blocks, etc.) are affected. Unlike previous schemes, our evaluation method has a canonical representation of ground-truth data and guarantees pixel-accurate evaluation results for arbitrary region shapes. We present the results of evaluating widely used segmentation algorithms (x-y cut, smearing, whitespace analysis, constrained text-line finding, docstrum, and Voronoi) on the UW-III database and demonstrate that the new evaluation scheme permits the identification of several specific flaws in individual segmentation methods.
204 citations
PARC1
TL;DR: Geometric algorithms for solving two key problems in layout analysis: finding a cover of the background whitespace of a document in terms of maximal empty rectangles and finding constrained maximum likelihood matches of geometric text line models in the presence of geometric obstacles are presented.
Abstract: This paper presents geometric algorithms for solving two key problems in layout analysis: finding a cover of the background whitespace of a document in terms of maximal empty rectangles, and finding constrained maximum likelihood matches of geometric text line models in the presence of geometric obstacles. The algorithms are considerably easier to implement than prior methods, they return globally optimal solutions, and they require no heuristics. The paper also introduces an evaluation function that reliably identifies maximal empty rectangles corresponding to column boundaries. Combining this evaluation function with the two geometric algorithms results in an easy-to-implement layout analysis system. Reliability of the system is demonstrated on documents from the UW3 database.
191 citations
Cites background from "Segmentation of Page Images Using t..."
...Background structure analysis as an approach to document layout analysis has been described by a number of authors [13, 2, 12, 8, 1, 9]....
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TL;DR: A novel text line segmentation algorithm based on minimal spanning tree (MST) clustering with distance metric learning that is made robust to handle various documents with multi-skewed and curved text lines.
155 citations
Cites methods from "Segmentation of Page Images Using t..."
...To do this, we construct the area Voronoi diagram [20] of the training document, which represents the spatial adjacency between the...
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References
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Book•
01 Jan 1992TL;DR: In this article, the Voronoi diagram generalizations of the Voroni diagram algorithm for computing poisson Voroni diagrams are defined and basic properties of the generalization of Voroni's algorithm are discussed.
Abstract: Definitions and basic properties of the Voronoi diagram generalizations of the Voronoi diagram algorithms for computing Voronoi diagrams poisson Voronoi diagrams spatial interpolation models of spatial processes point pattern analysis locational optimization through Voronoi diagrams.
4,018 citations
TL;DR: The development and implementation of an algorithm for automated text string separation that is relatively independent of changes in text font style and size and of string orientation are described and showed superior performance compared to other techniques.
Abstract: The development and implementation of an algorithm for automated text string separation that is relatively independent of changes in text font style and size and of string orientation are described. It is intended for use in an automated system for document analysis. The principal parts of the algorithm are the generation of connected components and the application of the Hough transform in order to group components into logical character strings that can then be separated from the graphics. The algorithm outputs two images, one containing text strings and the other graphics. These images can then be processed by suitable character recognition and graphics recognition systems. The performance of the algorithm, both in terms of its effectiveness and computational efficiency, was evaluated using several test images and showed superior performance compared to other techniques. >
664 citations
"Segmentation of Page Images Using t..." refers methods in this paper
...Fletcher and Kasturi have utilized four nearest neighbors within a collinear group of connected components [5]....
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TL;DR: The document spectrum (or docstrum) as discussed by the authors is a method for structural page layout analysis based on bottom-up, nearest-neighbor clustering of page components, which yields an accurate measure of skew, within-line, and between-line spacings and locates text lines and text blocks.
Abstract: Page layout analysis is a document processing technique used to determine the format of a page. This paper describes the document spectrum (or docstrum), which is a method for structural page layout analysis based on bottom-up, nearest-neighbor clustering of page components. The method yields an accurate measure of skew, within-line, and between-line spacings and locates text lines and text blocks. It is advantageous over many other methods in three main ways: independence from skew angle, independence from different text spacings, and the ability to process local regions of different text orientations within the same image. Results of the method shown for several different page formats and for randomly oriented subpages on the same image illustrate the versatility of the method. We also discuss the differences, advantages, and disadvantages of the docstrum with respect to other lay-out methods. >
654 citations
Book•
01 Jan 1995
TL;DR: The document spectrum (or docstrum), which is a method for structural page layout analysis based on bottom-up, nearest-neighbor clustering of page components, yields an accurate measure of skew, within-line, and between-line spacings and locates text lines and text blocks.
Abstract: Page layout analysis is a document processing technique used to determine the format of a page. This paper describes the document spectrum (or docstrum), which is a method for structural page layout analysis based on bottom-up, nearest-neighbor clustering of page components. The method yields an accurate measure of skew, within-line, and between-line spacings and locates text lines and text blocks. It is advantageous over many other methods in three main ways: independence from skew angle, independence from different text spacings, and the ability to process local regions of different text orientations within the same image. Results of the method shown for several different page formats and for randomly oriented subpages on the same image illustrate the versatility of the method. We also discuss the differences, advantages, and disadvantages of the docstrum with respect to other lay-out methods. >
628 citations
"Segmentation of Page Images Using t..." refers background in this paper
...O’Gorman has focused on k- earest neighbors to form blocks as well as text-lines from connected components [6]....
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