OcrV1, PubMed, Corpus, bibRecord, 000064

Restoring warped document images through 3D shape modeling.

Identifieur interne : 000064 ( PubMed/Corpus ); précédent : 000063; suivant : 000065

Restoring warped document images through 3D shape modeling.

Auteurs : Chew Lim Tan ; Li Zhang ; Zheng Zhang ; Tao Xia

Source :

IEEE transactions on pattern analysis and machine intelligence [ 0162-8828 ] ; 2006.

RBID : pubmed:16468617

English descriptors

KwdEn :
- Algorithms, Artifacts, Artificial Intelligence, Automatic Data Processing (methods), Computer Graphics, Computer Simulation, Documentation (methods), Image Enhancement (methods), Image Interpretation, Computer-Assisted (methods), Imaging, Three-Dimensional (methods), Information Storage and Retrieval (methods), Models, Theoretical, Pattern Recognition, Automated (methods), Reproducibility of Results, Sensitivity and Specificity.
MESH :
- methods : Automatic Data Processing, Documentation, Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Information Storage and Retrieval, Pattern Recognition, Automated.
- Algorithms, Artifacts, Artificial Intelligence, Computer Graphics, Computer Simulation, Models, Theoretical, Reproducibility of Results, Sensitivity and Specificity.

Abstract

Scanning a document page from a thick bound volume often results in two kinds of distortions in the scanned image, i.e., shade along the "spine" of the book and warping in the shade area. In this paper, we propose an efficient restoration method based on the discovery of the 3D shape of a book surface from the shading information in a scanned document image. From a technical point of view, this shape from shading (SFS) problem in real-world environments is characterized by 1) a proximal and moving light source, 2) Lambertian reflection, 3) nonuniform albedo distribution, and 4) document skew. Taking all these factors into account, we first build practical models (consisting of a 3D geometric model and a 3D optical model) for the practical scanning conditions to reconstruct the 3D shape of the book surface. We next restore the scanned document image using this shape based on deshading and dewarping models. Finally, we evaluate the restoration results by comparing our estimated surface shape with the real shape as well as the OCR performance on original and restored document images. The results show that the geometric and photometric distortions are mostly removed and the OCR results are improved markedly.

DOI: 10.1109/TPAMI.2006.40
PubMed: 16468617

Links to Exploration step

pubmed:16468617

Le document en format XML

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<author><name sortKey="Zhang, Li" sort="Zhang, Li" uniqKey="Zhang L" first="Li" last="Zhang">Li Zhang</name>
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<author><name sortKey="Zhang, Zheng" sort="Zhang, Zheng" uniqKey="Zhang Z" first="Zheng" last="Zhang">Zheng Zhang</name>
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<author><name sortKey="Xia, Tao" sort="Xia, Tao" uniqKey="Xia T" first="Tao" last="Xia">Tao Xia</name>
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<front><div type="abstract" xml:lang="en">Scanning a document page from a thick bound volume often results in two kinds of distortions in the scanned image, i.e., shade along the "spine" of the book and warping in the shade area. In this paper, we propose an efficient restoration method based on the discovery of the 3D shape of a book surface from the shading information in a scanned document image. From a technical point of view, this shape from shading (SFS) problem in real-world environments is characterized by 1) a proximal and moving light source, 2) Lambertian reflection, 3) nonuniform albedo distribution, and 4) document skew. Taking all these factors into account, we first build practical models (consisting of a 3D geometric model and a 3D optical model) for the practical scanning conditions to reconstruct the 3D shape of the book surface. We next restore the scanned document image using this shape based on deshading and dewarping models. Finally, we evaluate the restoration results by comparing our estimated surface shape with the real shape as well as the OCR performance on original and restored document images. The results show that the geometric and photometric distortions are mostly removed and the OCR results are improved markedly.</div>
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<Abstract><AbstractText>Scanning a document page from a thick bound volume often results in two kinds of distortions in the scanned image, i.e., shade along the "spine" of the book and warping in the shade area. In this paper, we propose an efficient restoration method based on the discovery of the 3D shape of a book surface from the shading information in a scanned document image. From a technical point of view, this shape from shading (SFS) problem in real-world environments is characterized by 1) a proximal and moving light source, 2) Lambertian reflection, 3) nonuniform albedo distribution, and 4) document skew. Taking all these factors into account, we first build practical models (consisting of a 3D geometric model and a 3D optical model) for the practical scanning conditions to reconstruct the 3D shape of the book surface. We next restore the scanned document image using this shape based on deshading and dewarping models. Finally, we evaluate the restoration results by comparing our estimated surface shape with the real shape as well as the OCR performance on original and restored document images. The results show that the geometric and photometric distortions are mostly removed and the OCR results are improved markedly.</AbstractText>
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Restoring warped document images through 3D shape modeling.

Restoring warped document images through 3D shape modeling.

Source :

English descriptors

Abstract

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

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