Wyszukiwarka
Improvement of Image Binarization Methods Using Image Preprocessing with Local Entropy Filtering for Alphanumerical Character Recognition Purposes
Abstrakt
Automatic text recognition from the natural images acquired in uncontrolled lighting conditions is a challenging task due to the presence of shadows hindering the shape analysis and classification of individual characters. Since the optical character recognition methods require prior image binarization, the application of classical global thresholding methods in such case makes it impossible to preserve the visibility of all characters. Nevertheless, the use of adaptive binarization does not always lead to satisfactory results for heavily unevenly illuminated document images. In this paper, the image preprocessing methodology with the use of local image entropy filtering is proposed, allowing for the improvement of various commonly used image thresholding methods, which can be useful also for text recognition purposes. The proposed approach was verified using a dataset of 140 differently illuminated document images subjected to further text recognition. Experimental results, expressed as Levenshtein distances and F-Measure values for obtained text strings, are promising and confirm the usefulness of the proposed approach.
Cytowania
-
4 8
CrossRef
-
0
Web of Science
-
5 3
Scopus
Cytuj jako
Pełna treść
pełna treść publikacji nie jest dostępna w portalu
Słowa kluczowe
Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- Publikacja w czasopiśmie
- Opublikowano w:
-
ENTROPY
nr 21,
wydanie 6,
ISSN: 1099-4300 - ISSN:
- 1099-4300
- Rok wydania:
- 2019
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.3390/e21060562
- Weryfikacja:
- Brak weryfikacji
wyświetlono 19 razy
Publikacje, które mogą cię zainteresować
Preprocessing of Document Images Based on the GGD and GMM for Binarization of Degraded Ancient Papyri Images
- H. Michalak,
- R. Krupiński,
- P. Lech
- + 1 autorów