OcrV1, PascalFrancis, Corpus, bibRecord, 000043

Text extraction from natural scene image: A survey

Identifieur interne : 000043 ( PascalFrancis/Corpus ); précédent : 000042; suivant : 000044

Text extraction from natural scene image: A survey

Auteurs : HONGGANG ZHANG ; KAILI ZHAO ; Yi-Zhe Song ; JUN GUO

Source :

Neurocomputing : (Amsterdam) [ 0925-2312 ] ; 2013.

RBID : Pascal:13-0324769

Descripteurs français

Pascal (Inist)
- Extraction information, Texte, Analyse scène, Calculateur embarqué, Traitement image, Réalité virtuelle, Interface utilisateur, Recherche information, Vision ordinateur, Localisation, Reconnaissance optique caractère, Reconnaissance caractère, Appareil photographique, Réalité augmentée, Alignement, Luminance, Procédé extraction, Extraction forme, Algorithmique, Segmentation, Eclairement, Scène naturelle, Accentuation image, Traitement image document.

English descriptors

KwdEn :
- Algorithmics, Alignment, Augmented reality, Boarded computer, Camera, Character recognition, Computer vision, Document image processing, Extraction process, Illumination, Image enhancement, Image processing, Information extraction, Information retrieval, Localization, Luminance, Natural scenes, Optical character recognition, Pattern extraction, Scene analysis, Segmentation, Text, User interface, Virtual reality.

Abstract

With the increasing popularity of portable camera devices and embedded visual processing, text extraction from natural scene images has become a key problem that is deemed to change our everyday lives via novel applications such as augmented reality. Text extraction from natural scene images algorithms is generally composed of the following three stages: (i) detection and localization, (ii) text enhancement and segmentation and (iii) optical character recognition (OCR). The problem is challenging in nature due to variations in the font size and color, text alignment, illumination change and reflections. This paper aims to classify and assess the latest algorithms. More specifically, we draw attention to studies on the first two steps in the extraction process, since OCR is a well-studied area where powerful algorithms already exist. This paper offers to the researchers a link to public image database for the algorithm assessment of text extraction from natural scene images.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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Format Inist (serveur)

NO :	PASCAL 13-0324769 INIST
ET :	Text extraction from natural scene image: A survey
AU :	HONGGANG ZHANG; KAILI ZHAO; SONG (Yi-Zhe); JUN GUO
AF :	School of Communication and Information Engineering, Beijing University of Posts and Telecommunications/Beijing/Chine (1 aut., 2 aut., 4 aut.); School of Electronic Engineering and Computer Science, Queen Mary, University of London/London E1 4NS/Royaume-Uni (3 aut.)
DT :	Publication en série; Niveau analytique
SO :	Neurocomputing : (Amsterdam); ISSN 0925-2312; Pays-Bas; Da. 2013; Vol. 122; Pp. 310-323; Bibl. 91 ref.
LA :	Anglais
EA :	With the increasing popularity of portable camera devices and embedded visual processing, text extraction from natural scene images has become a key problem that is deemed to change our everyday lives via novel applications such as augmented reality. Text extraction from natural scene images algorithms is generally composed of the following three stages: (i) detection and localization, (ii) text enhancement and segmentation and (iii) optical character recognition (OCR). The problem is challenging in nature due to variations in the font size and color, text alignment, illumination change and reflections. This paper aims to classify and assess the latest algorithms. More specifically, we draw attention to studies on the first two steps in the extraction process, since OCR is a well-studied area where powerful algorithms already exist. This paper offers to the researchers a link to public image database for the algorithm assessment of text extraction from natural scene images.
CC :	001D02C03; 001D02C04; 001D02B04; 001D02A05
FD :	Extraction information; Texte; Analyse scène; Calculateur embarqué; Traitement image; Réalité virtuelle; Interface utilisateur; Recherche information; Vision ordinateur; Localisation; Reconnaissance optique caractère; Reconnaissance caractère; Appareil photographique; Réalité augmentée; Alignement; Luminance; Procédé extraction; Extraction forme; Algorithmique; Segmentation; Eclairement; Scène naturelle; Accentuation image; Traitement image document
ED :	Information extraction; Text; Scene analysis; Boarded computer; Image processing; Virtual reality; User interface; Information retrieval; Computer vision; Localization; Optical character recognition; Character recognition; Camera; Augmented reality; Alignment; Luminance; Extraction process; Pattern extraction; Algorithmics; Segmentation; Illumination; Natural scenes; Image enhancement; Document image processing
SD :	Extracción información; Texto; Análisis escena; Calculador embarque; Procesamiento imagen; Realidad virtual; Interfase usuario; Búsqueda información; Visión ordenador; Localización; Reconocimento óptico de caracteres; Reconocimiento carácter; Máquina fotográfica; Realidad aumentada; Alineamiento; Luminancia; Procedimiento extracción; Extracción forma; Algorítmica; Segmentación; Alumbrado; Escena natural; Mejoramiento de imágenes; Tratamiento de imágenes de documentos
LO :	INIST-28121.354000501570810320
ID :	13-0324769

Links to Exploration step

Pascal:13-0324769

Le document en format XML

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<front><div type="abstract" xml:lang="en">With the increasing popularity of portable camera devices and embedded visual processing, text extraction from natural scene images has become a key problem that is deemed to change our everyday lives via novel applications such as augmented reality. Text extraction from natural scene images algorithms is generally composed of the following three stages: (i) detection and localization, (ii) text enhancement and segmentation and (iii) optical character recognition (OCR). The problem is challenging in nature due to variations in the font size and color, text alignment, illumination change and reflections. This paper aims to classify and assess the latest algorithms. More specifically, we draw attention to studies on the first two steps in the extraction process, since OCR is a well-studied area where powerful algorithms already exist. This paper offers to the researchers a link to public image database for the algorithm assessment of text extraction from natural scene images.</div>
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<s5>10</s5>
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<s5>10</s5>
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<s5>15</s5>
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<s5>25</s5>
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<s5>41</s5>
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<s5>41</s5>
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<fC03 i1="22" i2="X" l="FRE"><s0>Scène naturelle</s0>
<s4>CD</s4>
<s5>96</s5>
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<s4>CD</s4>
<s5>96</s5>
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<s4>CD</s4>
<s5>96</s5>
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<fC03 i1="23" i2="X" l="FRE"><s0>Accentuation image</s0>
<s4>CD</s4>
<s5>97</s5>
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<s4>CD</s4>
<s5>97</s5>
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<s4>CD</s4>
<s5>97</s5>
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<s4>CD</s4>
<s5>98</s5>
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<fC03 i1="24" i2="X" l="SPA"><s0>Tratamiento de imágenes de documentos</s0>
<s4>CD</s4>
<s5>98</s5>
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<fN82><s1>OTO</s1>
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<server><NO>PASCAL 13-0324769 INIST</NO>
<ET>Text extraction from natural scene image: A survey</ET>
<AU>HONGGANG ZHANG; KAILI ZHAO; SONG (Yi-Zhe); JUN GUO</AU>
<AF>School of Communication and Information Engineering, Beijing University of Posts and Telecommunications/Beijing/Chine (1 aut., 2 aut., 4 aut.); School of Electronic Engineering and Computer Science, Queen Mary, University of London/London E1 4NS/Royaume-Uni (3 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>Neurocomputing : (Amsterdam); ISSN 0925-2312; Pays-Bas; Da. 2013; Vol. 122; Pp. 310-323; Bibl. 91 ref.</SO>
<LA>Anglais</LA>
<EA>With the increasing popularity of portable camera devices and embedded visual processing, text extraction from natural scene images has become a key problem that is deemed to change our everyday lives via novel applications such as augmented reality. Text extraction from natural scene images algorithms is generally composed of the following three stages: (i) detection and localization, (ii) text enhancement and segmentation and (iii) optical character recognition (OCR). The problem is challenging in nature due to variations in the font size and color, text alignment, illumination change and reflections. This paper aims to classify and assess the latest algorithms. More specifically, we draw attention to studies on the first two steps in the extraction process, since OCR is a well-studied area where powerful algorithms already exist. This paper offers to the researchers a link to public image database for the algorithm assessment of text extraction from natural scene images.</EA>
<CC>001D02C03; 001D02C04; 001D02B04; 001D02A05</CC>
<FD>Extraction information; Texte; Analyse scène; Calculateur embarqué; Traitement image; Réalité virtuelle; Interface utilisateur; Recherche information; Vision ordinateur; Localisation; Reconnaissance optique caractère; Reconnaissance caractère; Appareil photographique; Réalité augmentée; Alignement; Luminance; Procédé extraction; Extraction forme; Algorithmique; Segmentation; Eclairement; Scène naturelle; Accentuation image; Traitement image document</FD>
<ED>Information extraction; Text; Scene analysis; Boarded computer; Image processing; Virtual reality; User interface; Information retrieval; Computer vision; Localization; Optical character recognition; Character recognition; Camera; Augmented reality; Alignment; Luminance; Extraction process; Pattern extraction; Algorithmics; Segmentation; Illumination; Natural scenes; Image enhancement; Document image processing</ED>
<SD>Extracción información; Texto; Análisis escena; Calculador embarque; Procesamiento imagen; Realidad virtual; Interfase usuario; Búsqueda información; Visión ordenador; Localización; Reconocimento óptico de caracteres; Reconocimiento carácter; Máquina fotográfica; Realidad aumentada; Alineamiento; Luminancia; Procedimiento extracción; Extracción forma; Algorítmica; Segmentación; Alumbrado; Escena natural; Mejoramiento de imágenes; Tratamiento de imágenes de documentos</SD>
<LO>INIST-28121.354000501570810320</LO>
<ID>13-0324769</ID>
</server>
</inist>
</record>

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Text extraction from natural scene image: A survey

Text extraction from natural scene image: A survey

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