Crossing Number Features: From Biometrics to Printed Character Matching
| Autor: | Pauline Puteaux, Iuliia Tkachenko |
|---|---|
| Přispěvatelé: | Image & Interaction (ICAR), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2) |
| Rok vydání: | 2021 |
| Předmět: |
Matching (statistics)
Biometrics Generalization Computer science Feature extraction 0211 other engineering and technologies 02 engineering and technology Skeletonization 0202 electrical engineering electronic engineering information engineering [INFO]Computer Science [cs] Printed document 021110 strategic defence & security studies Print-and-scan process business.industry Template matching Pattern recognition Crossing numbers [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing Character (mathematics) Feature (computer vision) [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] 020201 artificial intelligence & image processing Artificial intelligence Matching method business |
| Zdroj: | Document Analysis and Recognition – ICDAR 2021 Workshops ISBN: 9783030861971 ICDAR Workshops (1) 3rd International Workshop on Computational Document Forensics (IWCDF 2021) 3rd International Workshop on Computational Document Forensics (IWCDF 2021), Sep 2021, Lausanne, Switzerland |
| DOI: | 10.1007/978-3-030-86198-8_31 |
| Popis: | International audience; Nowadays, the security of both digital and hardcopy documents has become a real issue. As a solution, numerous integrity check approaches have been designed. The challenge lies in finding features which are robust to print-and-scan process. In this paper, we propose a new method of printed-and-scanned character matching based on the adaptation of biometrical features. After the binarization and the skeletonization of a character, feature points are extracted by computing crossing numbers. The feature point set can then be smoothed to make it more suitable for template matching. From various experimental results, we have shown that an accuracy of more than 95% is achieved for printand-scan resolutions of 300 dpi and 600 dpi. We have also highlighted the feasibility of the proposed method in case of double print-and-scan operation. The comparison with a state-of-the-art method shows that the generalization of proposed matching method is possible while using different fonts. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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