OcrV1, PascalFrancis, Corpus, bibRecord, 000099

Intelligent region-based thresholding for color document images with highlighted regions

Identifieur interne : 000099 ( PascalFrancis/Corpus ); précédent : 000098; suivant : 000100

Intelligent region-based thresholding for color document images with highlighted regions

Auteurs : Chun-Ming Tsai

Source :

Pattern recognition [ 0031-3203 ] ; 2012.

RBID : Pascal:12-0135276

Descripteurs français

Pascal (Inist)
- Détection seuil, Image couleur, Traitement image document, Evaluation performance, Diminution coût, Complexité calcul, Reconnaissance optique caractère, Eclairement, Qualité image, Algorithme, Système embarqué, Reconnaissance forme, Arrière plan, Avant plan.

English descriptors

KwdEn :
- Algorithm, Background, Color image, Computational complexity, Cost lowering, Document image processing, Embedded systems, Foreground, Illumination, Image quality, Optical character recognition, Pattern recognition, Performance evaluation, Threshold detection.

Abstract

The study applies an intelligent region-based thresholding method for the binarization of color document images with highlighted regions. The results also indicate that the proposed method can threshold simultaneously when the background is gradually changing, reversed, or inseparable from the foreground, with efficient binarization results. Rather than the traditional method of scanning the entire document at least once, this method intelligently divides a document image into several foreground regions and decides the background range for each foreground region, in order to effectively process the detected document regions. Experimental results demonstrate the high effectiveness of the proposed method in providing promising binarization results with low computational cost. Furthermore, the results of the proposed method are more accurate than global, region-based, local, and hybrid methods. Images were analyzed using MODI OCR measurement data such as recall rate and precision rate. In particular, when test images produced under inadequate illumination are processed using the proposed method, the binarization results of this method have better visual quality and better measurable OCR performance than compared global, region-based, local, and hybrid methods. Moreover, the proposed algorithm can be run in an embedded system due to its simplicity and efficiency.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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Format Inist (serveur)

NO :	PASCAL 12-0135276 INIST
ET :	Intelligent region-based thresholding for color document images with highlighted regions
AU :	TSAI (Chun-Ming)
AF :	Department of Computer Science, Taipei Municipal University of Education, No. 1, Ai-Kuo W. Road/Taipei 100/Taïwan (1 aut.)
DT :	Publication en série; Niveau analytique
SO :	Pattern recognition; ISSN 0031-3203; Coden PTNRA8; Royaume-Uni; Da. 2012; Vol. 45; No. 4; Pp. 1341-1362; Bibl. 23 ref.
LA :	Anglais
EA :	The study applies an intelligent region-based thresholding method for the binarization of color document images with highlighted regions. The results also indicate that the proposed method can threshold simultaneously when the background is gradually changing, reversed, or inseparable from the foreground, with efficient binarization results. Rather than the traditional method of scanning the entire document at least once, this method intelligently divides a document image into several foreground regions and decides the background range for each foreground region, in order to effectively process the detected document regions. Experimental results demonstrate the high effectiveness of the proposed method in providing promising binarization results with low computational cost. Furthermore, the results of the proposed method are more accurate than global, region-based, local, and hybrid methods. Images were analyzed using MODI OCR measurement data such as recall rate and precision rate. In particular, when test images produced under inadequate illumination are processed using the proposed method, the binarization results of this method have better visual quality and better measurable OCR performance than compared global, region-based, local, and hybrid methods. Moreover, the proposed algorithm can be run in an embedded system due to its simplicity and efficiency.
CC :	001D04A05C; 001D04A05A; 001D04A04A2
FD :	Détection seuil; Image couleur; Traitement image document; Evaluation performance; Diminution coût; Complexité calcul; Reconnaissance optique caractère; Eclairement; Qualité image; Algorithme; Système embarqué; Reconnaissance forme; Arrière plan; Avant plan
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EG :	Image processing
SD :	Detección umbral; Imagen color; Evaluación prestación; Reducción costes; Complejidad computación; Reconocimento óptico de caracteres; Alumbrado; Calidad imagen; Algoritmo; Reconocimiento patrón
LO :	INIST-15220.354000502889930110
ID :	12-0135276

Links to Exploration step

Pascal:12-0135276

Le document en format XML

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<ET>Intelligent region-based thresholding for color document images with highlighted regions</ET>
<AU>TSAI (Chun-Ming)</AU>
<AF>Department of Computer Science, Taipei Municipal University of Education, No. 1, Ai-Kuo W. Road/Taipei 100/Taïwan (1 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
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<LA>Anglais</LA>
<EA>The study applies an intelligent region-based thresholding method for the binarization of color document images with highlighted regions. The results also indicate that the proposed method can threshold simultaneously when the background is gradually changing, reversed, or inseparable from the foreground, with efficient binarization results. Rather than the traditional method of scanning the entire document at least once, this method intelligently divides a document image into several foreground regions and decides the background range for each foreground region, in order to effectively process the detected document regions. Experimental results demonstrate the high effectiveness of the proposed method in providing promising binarization results with low computational cost. Furthermore, the results of the proposed method are more accurate than global, region-based, local, and hybrid methods. Images were analyzed using MODI OCR measurement data such as recall rate and precision rate. In particular, when test images produced under inadequate illumination are processed using the proposed method, the binarization results of this method have better visual quality and better measurable OCR performance than compared global, region-based, local, and hybrid methods. Moreover, the proposed algorithm can be run in an embedded system due to its simplicity and efficiency.</EA>
<CC>001D04A05C; 001D04A05A; 001D04A04A2</CC>
<FD>Détection seuil; Image couleur; Traitement image document; Evaluation performance; Diminution coût; Complexité calcul; Reconnaissance optique caractère; Eclairement; Qualité image; Algorithme; Système embarqué; Reconnaissance forme; Arrière plan; Avant plan</FD>
<FG>Traitement image</FG>
<ED>Threshold detection; Color image; Document image processing; Performance evaluation; Cost lowering; Computational complexity; Optical character recognition; Illumination; Image quality; Algorithm; Embedded systems; Pattern recognition; Background; Foreground</ED>
<EG>Image processing</EG>
<SD>Detección umbral; Imagen color; Evaluación prestación; Reducción costes; Complejidad computación; Reconocimento óptico de caracteres; Alumbrado; Calidad imagen; Algoritmo; Reconocimiento patrón</SD>
<LO>INIST-15220.354000502889930110</LO>
<ID>12-0135276</ID>
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Intelligent region-based thresholding for color document images with highlighted regions

Intelligent region-based thresholding for color document images with highlighted regions

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