Results 251 to 260 of about 2,296,500 (293)

Document image analysis for active reading

Proceedings of the 2007 international workshop on Semantically aware document processing and indexing, 2007
A huge number of documents that were only available in libraries are now on the web. The web access is a solution to protect the cultural heritage and to facilitate knowledge transmission. Most of these documents are displayed as images of the original paper pages and are indexed by hand.
Claudie Faure, Nicole Vincent
openaire   +1 more source

Dewarping Document Image by Displacement Flow Estimation with Fully Convolutional Network

International Workshop on Document Analysis Systems, 2020
As camera-based documents are increasingly used, the rectification of distorted document images becomes a need to improve the recognition performance. In this paper, we propose a novel framework for both rectifying distorted document image and removing ...
Guo-Wang Xie, Fei Yin, Xu-Yao Zhang, Chenglin Liu   +3 more
semanticscholar   +1 more source

Features for printed document image analysis

Object recognition supported by user interaction for service robots, 2003
This paper presents features for text/non-text area separation in printed document images. First, it introduces entropic discrimination, i.e., a simple separation using only one feature. Then, a brief recall on existing texture and geometric discriminant parameters proposed in previous research (2001, 2002) is included.
Jean Duong, Hubert Emptoz, Myriam Côté
openaire   +1 more source

Document Image Binarization Using Dual Discriminator Generative Adversarial Networks

IEEE Signal Processing Letters, 2020
For 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
semanticscholar   +1 more source

Treatment of Diagrams in Document Image Analysis

2000
Document image analysis is the study of converting documents from paper form to an electronic form that captures the information content of the document. Necessary processing includes recognition of document layout (to determine reading order, and to distinguish text from diagrams), recognition of text (called Optical Character Recognition, OCR), and ...
Dorothea Blostein, Edward Lank, Richard Zanibbi   +2 more
openaire   +1 more source

Handwritten document image segmentation and analysis

Pattern Recognition Letters, 1993
Abstract 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, Georgi Gluhchev, Vassil Stoyanov Sgurev   +2 more
openaire   +1 more source

Visual and Textual Deep Feature Fusion for Document Image Classification

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020
The 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, Zuheng Ming, Mickaël Coustaty, Marçal Rusiñol   +3 more
semanticscholar   +1 more source

XML Data Representation in Document Image Analysis

Ninth International Conference on Document Analysis and Recognition (ICDAR 2007), 2007
This 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, Falk, Ingrid, Rangoni, Yves   +2 more
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Watershed Based Document Image Analysis

2010
Document 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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Document image analysis with OCRopus

2009 IEEE 13th International Multitopic Conference, 2009
Document image analysis is the field of converting paper documents into an editable electronic representation by performing optical character recognition (OCR). In recent years, there has been a tremendous amount of progress in the development of open source OCR systems.
openaire   +1 more source