OcrV1, Main, Exploration, bibRecord, 001C02

Fast real-time recognition and quality inspection of printed characters via point-correlation

Identifieur interne : 001C02 ( Main/Exploration ); précédent : 001C01; suivant : 001C03

Fast real-time recognition and quality inspection of printed characters via point-correlation

Auteurs : H. Penz [Autriche] ; I. Bajla [Autriche] ; A. Vrabl [Autriche] ; W. Krattenthaler [Autriche] ; K. Mayer [Autriche]

Source :

SPIE proceedings series [ 1017-2653 ] ; 2001.

RBID : Pascal:02-0062190

Descripteurs français

Pascal (Inist)
- Traitement image, Traitement temps réel, Caractère imprimé, Reconnaissance caractère, Inspection, Qualité image, Concordance forme, Corrélation, Algorithme.

English descriptors

KwdEn :
- Algorithm, Character recognition, Correlation, Image processing, Image quality, Inspection, Pattern matching, Printed character, Real time processing.

Abstract

Some technical applications need a fast and reliable OCR (optical character recognition) for critical circumstances like low resolution and poor contrast. A concrete example is the real-time quality inspection system of Austrian banknotes. One requirement to the system is that it has to read two serial numbers on each banknote and to check if they are identical. To solve the problem we have developed a novel method based on an idea similar to pattern matching. However, instead of comparing entire images we use reduced sets of pixels, one for each different numeral (character). The detection (point correlation) is performed by matching these pixel sets with the corresponding pixels in the image being analyzed. We present an algorithm based on two cost functions that computes in a reasonable time the reduced pixel (point) sets from a given set of image templates. The efficiency of our OCR has been increased considerably by introducing an appropriate set of image preprocessing operations. These are tailored especially to images with low resolution and poor contrast, but they are simple enough to allow a fast real-time implementation. They can be seen as a normalization step that improves the image properties which are essential for pattern matching.

Affiliations:

Autriche

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

to stream PascalFrancis, to step Corpus: 000690
to stream PascalFrancis, to step Curation: 000102
to stream PascalFrancis, to step Checkpoint: 000671
to stream Main, to step Merge: 001C98
to stream Main, to step Curation: 001C02

Le document en format XML

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<front><div type="abstract" xml:lang="en">Some technical applications need a fast and reliable OCR (optical character recognition) for critical circumstances like low resolution and poor contrast. A concrete example is the real-time quality inspection system of Austrian banknotes. One requirement to the system is that it has to read two serial numbers on each banknote and to check if they are identical. To solve the problem we have developed a novel method based on an idea similar to pattern matching. However, instead of comparing entire images we use reduced sets of pixels, one for each different numeral (character). The detection (point correlation) is performed by matching these pixel sets with the corresponding pixels in the image being analyzed. We present an algorithm based on two cost functions that computes in a reasonable time the reduced pixel (point) sets from a given set of image templates. The efficiency of our OCR has been increased considerably by introducing an appropriate set of image preprocessing operations. These are tailored especially to images with low resolution and poor contrast, but they are simple enough to allow a fast real-time implementation. They can be seen as a normalization step that improves the image properties which are essential for pattern matching.</div>
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Fast real-time recognition and quality inspection of printed characters via point-correlation

Fast real-time recognition and quality inspection of printed characters via point-correlation

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