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Handwritten document image segmentation and analysis
Pattern Recognition Letters, 1993Abstract The paper proposes automatic segmentation of handwritten document binary images. The Hough transform (HT) over the source image is applied and then the slope of handwritten rows is estimated by analyzing the parameter plane. The inverse HT is used for ‘cutting’ the image and forming ‘strips’, containing the respective handwritten rows ...
Vladimir A. Shapiro +2 more
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XML Data Representation in Document Image Analysis
Ninth International Conference on Document Analysis and Recognition (ICDAR 2007), 2007This paper presents the XML-based formats ALTO, TEI, METS used for Digital Libraries and their interest for data representation in a Document Image Analysis and Recognition (DIAR) process. In the first part we briefly present these formats with focus on their adequacy for structural representation and modeling of DIAR data.
Belaid, Abdel +2 more
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Document Image Binarization Using Dual Discriminator Generative Adversarial Networks
IEEE Signal Processing Letters, 2020For document image analysis, image binarization is an important preprocessing step. Also, binarization can help in improving the readability of old and historical manuscripts.
R. De, Anuran Chakraborty, R. Sarkar
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Watershed Based Document Image Analysis
2010Document image analysis is used to segment and classify regions of a document image into categories such as text, graphic and background. In this paper we first review existing document image analysis approaches and discuss their limits. Then we adapt the well-known watershed segmentation in order to obtain a very fast and efficient classification ...
Pasha Shadkami, Nicolas Bonnier
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Layout Analysis of Document Images
LatinX in AI at Computer Vision and Pattern Recognition Conference 2023, 2023In order to extract information of interest from document images, their content must be recognized. To that end, layout analysis is an important step. In layout analysis one is concerned in finding page components such as text blocks, tables, formulas, diagrams, and determining their logical role.
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Visual and Textual Deep Feature Fusion for Document Image Classification
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020The topic of text document image classification has been explored extensively over the past few years. Most recent approaches handled this task by jointly learning the visual features of document images and their corresponding textual contents.
Souhail Bakkali +3 more
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Document image analysis for digital libraries
Proceedings of the 2006 international workshop on Research issues in digital libraries, 2006Digital Libraries have many forms -- institutional libraries for information dissemination, document repositories for record-keeping, and personal digital libraries for organizing personal thoughts, knowledge, and course of action. Digital image content (scanned or otherwise) is a substantial component of all of these libraries.
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2011
One of the main distinguishing features of a document is its layout, as determined by the organization of, and reciprocal relationships among, the single components that make it up. For many tasks, one can afford to work at the level of single pages, since the various pages in multi-page documents are usually sufficiently unrelated to be processed ...
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One of the main distinguishing features of a document is its layout, as determined by the organization of, and reciprocal relationships among, the single components that make it up. For many tasks, one can afford to work at the level of single pages, since the various pages in multi-page documents are usually sufficiently unrelated to be processed ...
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Document image binarization with cascaded generators of conditional generative adversarial networks
Pattern Recognition, 2019Binarization is often the first step in many document analysis tasks and plays a key role in the subsequent steps. In this paper, we formulate binarization as an image-to-image generation task and introduce the conditional generative adversarial networks
Jinyuan Zhao +4 more
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Multimodal Document Image Classification
IEEE International Conference on Document Analysis and Recognition, 2019State-of-the-art methods for document image classification rely on visual features extracted by deep convolutional neural networks (CNNs). These methods do not utilize rich semantic information present in the text of the document, which can be extracted ...
R. Jain, Curtis Wigington
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