New optical character recognition method based on Hu invariant moments and weighted voting

• Autorzy: Kmieć M.
• Języki publikacji: EN

Abstrakty

EN

Optical character recognition is an important image processing task. Its aim is to enable computers to recognise graphic characters without human supervision. The process of optical symbol recognition is divided into two stages. First, certain features of the character undergoing recognition are extracted, and second, a match to them is searched for in the library of models. This paper looks at Hu invariant moments, a well established set of image features, and discusses their performance in optical character recognition. One approach to using Hu invariant moments in pattern recognition is using a metric function to find the pattern in the library of models, that is of the same class as the pattern considered. In this paper a new classification method is proposed that performs better than the classic method of metric function.

Słowa kluczowe

EN

OCR; Hu invariant moments; image features; pattern classification

PL

OCR; momenty niezmienne Hu; cechy obrazu; rozpoznawanie obrazów

• Wydawca: Wydawnictwo Politechniki Łódzkiej
• Czasopismo: Journal of Applied Computer Science
• Rocznik: 2011
• Tom: Vol. 19, nr 1
• Strony: 33--50
• Opis fizyczny: Bibliogr. 5 poz.

Twórcy

autor

Kmieć M.

• AGH University of Science and Technology, Institute of Automatics, al. A. Mickiewicza 30, 30-059 Kraków,

Bibliografia

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• [2] Hu, M., Visual Pattern Recognition by Moment Invariants, IRE Transactions on Information Theory, 1962.
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• [4] Wolfe, P. and r, D., Elements of Photogrammetry with Applications to GIS, McGraw-Hill, 2000.
• [5] Bradsky, G. and Kaehler, A., Learning OpenCV. Computer Vision with the OpenCV Library, O'Reilly Media, 2008.