OcrV1, Main, Exploration, bibRecord, 000201

Document Scanning in a tough environment: application to cameraphones

Identifieur interne : 000201 ( Main/Exploration ); précédent : 000200; suivant : 000202

Document Scanning in a tough environment: application to cameraphones

Auteurs : Sahar Saoud [Maroc] ; Zouhir Mahani [Maroc] ; Abdelilah Hakim [Maroc] ; MOHAMMED EL RHABI [Maroc]

Source :

International journal of imaging and robotics [ 2231-525X ] ; 2013.

RBID : Pascal:13-0177193

Descripteurs français

Pascal (Inist)
- Numérisation, Texte, Eclairement, Equation dérivée partielle, Reconnaissance optique caractère, Reconnaissance caractère, Reconnaissance forme, Traitement image, Facteur réflexion, Luminance, Modélisation, Programmation non convexe, Fonction régulière, Robustesse, Algorithme approximation, Traitement image document, Accentuation image.
Wicri :
- topic : Numérisation.

English descriptors

KwdEn :
- Approximation algorithm, Character recognition, Digitizing, Document image processing, Illumination, Image enhancement, Image processing, Luminance, Modeling, Non convex programming, Optical character recognition, Partial differential equation, Pattern recognition, Reflectance, Robustness, Smooth function, Text.

Abstract

The aim of this paper is to suggest a new method to enhance text in document-image. In the first step, we present a classical model based on non-convex optimization problem. In this way, a simultaneous estimation of the reflectance and the luminance are obtained when the non uniform illumination (also called luminance) is a smooth function and the reflectance is a function of bounded variation. We prove some conditions of existence and unicity. Secondly, we introduce the "log" of the classical problem which generate a new PDE's model. Resolution of this method is based on solving an original Partial Differential Equation (PDE) estimating the log of the luminance. We assume that the luminance is enough smooth and is the solution of a non classical second order's PDE, and we deduce the reflectance from the estimated luminance and the acquired image. To illustrate the robustness of the proposed process (by means to prove the ability of this method to improve an Optical Character Recognition (OCR) in text recognition) we give a numerical examples in real-world situation (images acquired from cameraphones).

Affiliations:

Maroc

Links toward previous steps (curation, corpus...)

to stream PascalFrancis, to step Corpus: 000055
to stream PascalFrancis, to step Curation: 000713
to stream PascalFrancis, to step Checkpoint: 000044
to stream Main, to step Merge: 000204
to stream Main, to step Curation: 000201

Le document en format XML

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<term>Illumination</term>
<term>Image enhancement</term>
<term>Image processing</term>
<term>Luminance</term>
<term>Modeling</term>
<term>Non convex programming</term>
<term>Optical character recognition</term>
<term>Partial differential equation</term>
<term>Pattern recognition</term>
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<term>Reconnaissance caractère</term>
<term>Reconnaissance forme</term>
<term>Traitement image</term>
<term>Facteur réflexion</term>
<term>Luminance</term>
<term>Modélisation</term>
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<term>Fonction régulière</term>
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<front><div type="abstract" xml:lang="en">The aim of this paper is to suggest a new method to enhance text in document-image. In the first step, we present a classical model based on non-convex optimization problem. In this way, a simultaneous estimation of the reflectance and the luminance are obtained when the non uniform illumination (also called luminance) is a smooth function and the reflectance is a function of bounded variation. We prove some conditions of existence and unicity. Secondly, we introduce the "log" of the classical problem which generate a new PDE's model. Resolution of this method is based on solving an original Partial Differential Equation (PDE) estimating the log of the luminance. We assume that the luminance is enough smooth and is the solution of a non classical second order's PDE, and we deduce the reflectance from the estimated luminance and the acquired image. To illustrate the robustness of the proposed process (by means to prove the ability of this method to improve an Optical Character Recognition (OCR) in text recognition) we give a numerical examples in real-world situation (images acquired from cameraphones).</div>
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Serveur d'exploration sur l'OCR

Document Scanning in a tough environment: application to cameraphones

Document Scanning in a tough environment: application to cameraphones

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri