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Document Structure Analysis and Performance Evaluation
, 1999
"... Document Structure Analysis and Performance Evaluation by Jisheng Liang Chair of Supervisory Committee Professor Robert M. Haralick Electrical Engineering The goal of the document structure analysis is to find an optimal solution to partition the set of glyphs on a given document to a hierarchical t ..."
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Document Structure Analysis and Performance Evaluation by Jisheng Liang Chair of Supervisory Committee Professor Robert M. Haralick Electrical Engineering The goal of the document structure analysis is to find an optimal solution to partition the set of glyphs on a given document to a hierarchical tree structure where entities within the hierarchy are associated with their physical properties and semantic labels. In this dissertation, we present a unified document structure extraction algorithm that is probability based, where the probabilities are estimated from an extensive training set of various kinds of measurements of distances between the terminal and non-terminal entities with which the algorithm works. The off-line probabilities estimated in the training then drive all decisions in the on-line segmentation module. An iterative, relaxation like method is used to find the partitioning solution that maximizes the joint probability. This approach can be uniformly apply to the cons...
A New Table Extraction and Recovery Methodology with Little Use of Previous Knowledge
"... A new methodology for table-form extraction and recovery with little previous knowledge is presented. The first module performs the identification of line intersections in a table-form, the second module detects and corrects wrong intersections produced by fault intersection segments or by table art ..."
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A new methodology for table-form extraction and recovery with little previous knowledge is presented. The first module performs the identification of line intersections in a table-form, the second module detects and corrects wrong intersections produced by fault intersection segments or by table artefacts (smudges, overlapping of handwritten data and fault segments). In this module, an artefact identification method for handwritten filled table-forms is proposed. The proposed method aims to detect, identify and remove table-form artefacts with little use of previous knowledge. The third module performs the table-form cell extraction. The evaluation of the efficiency is carried out from a total of 305 table-form images. Experiments showed significant and promising results. The artefact identification method improves table-form interpretation rates. The proposed approach reached a successful rate up to 85%. The main advantage of the presented methodology is requiring little knowledge from documents, being able to apply for most of the table-forms.
Locating Charts from Scanned Document Pages
"... This paper presents our work on automatically locating charts from document pages, which is an important stage in our chart image recognition and understanding system currently being developed. To achieve this, there are two sub-goals to be reached: locating figure blocks in a given document image, ..."
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This paper presents our work on automatically locating charts from document pages, which is an important stage in our chart image recognition and understanding system currently being developed. To achieve this, there are two sub-goals to be reached: locating figure blocks in a given document image, and building a classifier to differentiate charts from nonchart figures. For the first sub-goal, besides traditional logical block labelling, relevant text blocks such as text descriptions and labels in a figure must be included in the located figure blocks to facilitate the interpretation processes in the following stages. For the second subgoal, we propose a set of simple statistical features for building the classifier. We tested our system with the entire collection of scanned journal pages in the University of Washington database I. The experimental results are discussed in this paper. 1.
Logical Block Labeling for Diverse Types of Document Images
"... Introduction 2. Segmentation components such as photos and figures occur in large bounding boxes, characters are contained in medium size boxes, and noise in small boxes. Segmentation proceeds by projecting the medium size boxes first vertically and then horizontally to detect gaps indicating col ..."
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Introduction 2. Segmentation components such as photos and figures occur in large bounding boxes, characters are contained in medium size boxes, and noise in small boxes. Segmentation proceeds by projecting the medium size boxes first vertically and then horizontally to detect gaps indicating columns and paragraph breaks [2]. In addition, large bounding boxes are further analyzed by projecting both the contained medium size bounding boxes and the pixels contained in the area in order to determine whether it is a framed text area or a table. Also, collinear large boxes of similar height are detected to recognize oversized headlines. This procedure distinguishes non-text and text regions at the paragraph level. We keep pointers to the coordinates of each block and all contained boxes to facilitate subsequent reading order determination and higher level layout analysis. The technique of analyzing small, medium, and large size boxes separatelyyields good segmentation results for overl
Table-form Extraction with Artefact Removal
"... Abstract: In this paper we present a novel methodology to recognize the layout structure of handwritten filled table-forms. Recognition methodology includes locating line intersections, correcting wrong intersections produced by what we call artefacts (overlapping data, broken segments and smudges), ..."
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Abstract: In this paper we present a novel methodology to recognize the layout structure of handwritten filled table-forms. Recognition methodology includes locating line intersections, correcting wrong intersections produced by what we call artefacts (overlapping data, broken segments and smudges), extracting correct table-form cells and using as little previous tableform knowledge as possible. To improve layout structure recognition, a novel artefact identification and deletion method is also proposed. To evaluate the effectiveness of the methodology, a database composed of 350 handwritten filled table-form images damaged by different types of artefacts was used. Experiments show that the artefact identification method improves performance of the table-forms structure extractor that reached a success rate of 85%. Keywords: Table-form recognition, Table-form extraction, Handwritten data, Document segmentation
A New Table Interpretation Methodology with Little Knowledge Base Table Interpretation Methodology
"... In this paper, a new methodology for table-form interpreta-tion with little previous knowledge is presented. The first module performs the identification of line intersections in a table-form, the second module detects and corrects wrong intersections produced by fault intersection segments or by ta ..."
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In this paper, a new methodology for table-form interpreta-tion with little previous knowledge is presented. The first module performs the identification of line intersections in a table-form, the second module detects and corrects wrong intersections produced by fault intersection segments or by table artefacts (smudges, overlapping of handwritten data and fault segments). The third module performs the table-form cell extraction. The features used to interpret the table-form are directly extracted from the image itself by means of morphological tools. The evaluation of the effi-ciency is carried out from a total of 305 table-form images. Experiments showed significant and promising results. The proposed approach reached a success rate over than 87 % on average. The main advantage of the proposed methodology is requiring little knowledge from documents, being able to apply for a table-form majority.
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"... Mass digitization of historical documents is a challenging problem for optical character recognition (OCR) tools. Issues include noisy backgrounds and faded text due to aging, border/marginal noise, bleed-through, skewing, warping, as well as irregular fonts and page layouts. As a result, OCR tools ..."
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Mass digitization of historical documents is a challenging problem for optical character recognition (OCR) tools. Issues include noisy backgrounds and faded text due to aging, border/marginal noise, bleed-through, skewing, warping, as well as irregular fonts and page layouts. As a result, OCR tools often produce a large number of spurious bounding boxes (BBs) in addition to those that correspond to words in the document. This paper presents an iterative classification algorithm to automatically label BBs (i.e., as text or noise) based on their spatial distribution and geometry. The approach uses a rule-base classifier to generate initial text/noise labels for each BB, followed by an iterative classifier that refines the initial labels by incorporating local information to each BB, its spatial
and
, 1999
"... This paper presents a performance metric for the document structure extraction algorithms by finding the correspondences between detected entities and ground truth. We describe a method for determining an algorithm’s optimal tuning param-eters. We evaluate a group of document layout analysis algorit ..."
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This paper presents a performance metric for the document structure extraction algorithms by finding the correspondences between detected entities and ground truth. We describe a method for determining an algorithm’s optimal tuning param-eters. We evaluate a group of document layout analysis algorithms on 1600 images from the UW-III Document Image Database, and the quantitative performance mea-sures in terms of the rates of correct, miss, false, merging, splitting, and spurious
Document layout analysis Seminar
, 2005
"... This document gives an overview about document layout analysis. It presents in detail one method which is part of the pre-processing phase, called skew angle estimation. In doing so it introduces a special technique of how determining the skew angle, namely the Hough Transform. Fur-thermore it prese ..."
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This document gives an overview about document layout analysis. It presents in detail one method which is part of the pre-processing phase, called skew angle estimation. In doing so it introduces a special technique of how determining the skew angle, namely the Hough Transform. Fur-thermore it presents numerous ways of approaches to speed up the process of skew angle detection. The second part deals with page segmentation which is one of the huge parts in document image analysis. It illustrates a means of partitioning using bounding boxes of different entities. It discusses advantages and
