OcrV1, Main, Exploration, bibRecord, 000762

Transition thresholds and transition operators for binarization and edge detection

Identifieur interne : 000762 ( Main/Exploration ); précédent : 000761; suivant : 000763

Transition thresholds and transition operators for binarization and edge detection

Auteurs : Marte A. Ramirez-Ortegon [Allemagne] ; Ernesto Tapia [Allemagne] ; Raúl Rojas [Allemagne] ; Erik Cuevas [Mexique]

Source :

Pattern recognition [ 0031-3203 ] ; 2010.

RBID : Pascal:10-0333641

Descripteurs français

Pascal (Inist)
- Détection contour, Image binaire, Classification non supervisée, Détection seuil, Histogramme, Evaluation performance, Reconnaissance optique caractère, Algorithme, Traitement image, Classification signal, Reconnaissance forme.

English descriptors

KwdEn :
- Algorithm, Binary image, Edge detection, Histogram, Image processing, Optical character recognition, Pattern recognition, Performance evaluation, Signal classification, Threshold detection, Unsupervised classification.

Abstract

The transition method for image binarization is based on the concept of t-transition pixels, a generalization of edge pixels, and t-transition sets. We introduce a novel unsupervised thresholding for unimodal histograms to estimate the transition sets. We also present dilation and incidence transition operators to refine the transition set. Afterward, we propose the simple edge transition operator for detecting edges. Our experiments show that the new approach increases the effectiveness of OCR applications outperforming several top-ranked binarization algorithms.

Affiliations:

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

to stream PascalFrancis, to step Corpus: 000177
to stream PascalFrancis, to step Curation: 000600
to stream PascalFrancis, to step Checkpoint: 000136
to stream Main, to step Merge: 000767
to stream Main, to step Curation: 000762

Le document en format XML

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<term>Evaluation performance</term>
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<front><div type="abstract" xml:lang="en">The transition method for image binarization is based on the concept of t-transition pixels, a generalization of edge pixels, and t-transition sets. We introduce a novel unsupervised thresholding for unimodal histograms to estimate the transition sets. We also present dilation and incidence transition operators to refine the transition set. Afterward, we propose the simple edge transition operator for detecting edges. Our experiments show that the new approach increases the effectiveness of OCR applications outperforming several top-ranked binarization algorithms.</div>
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Transition thresholds and transition operators for binarization and edge detection

Transition thresholds and transition operators for binarization and edge detection

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