Abstract
This paper describes a computer vision system designed to automatically read the displays of digital instrumentation. The system is used in calibration sessions where many measurements have to be made and where we are interested in getting the whole numerical series downloaded on a host computer. Before our system was running, a human operator had to inspect the instruments at the right times (required by the calibration procedure) and to write down all the results. Note that we are speaking of very simple and sometimes old instruments that usually do not provide a digital interface or a removable memory (and if they do, we do not have a standard interface accepted by all the manufacturers). Results show the benefits of this system, obtaining a success rate higher than 99% in display recognition
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ohya, J., Shio, A., Akamatsu, S.: Recognizing Characters in Scene Images. IEEE Transactions of Pattern Analysis and Machine Intelligence 16(2), 214–220 (1994)
Cowell, J.R.: Syntactic Pattern Recognizer for Vehicle Identification Numbers. Image & Vision Computing (1995)
Fernández-Hermida, X., et al.: Automatic and Real Time Recognition of V.L.P.’s (Vehicle License Plates). In: Del Bimbo, A. (ed.) ICIAP 1997. LNCS, vol. 1311, pp. 552–559. Springer, Heidelberg (1997)
Martín-Rodríguez, F., et al.: Localización de Caracteres en Imágenes de Instrumentación Digital. In: Proceedings of URSI-2009 (National Meeting of the International Scientific Radio Union). Santander, Spain (2009)
Otsu, N.: A Threshold Selection Method for Gray Level Histograms. IEEE Transactions on System, Man and Cybernetics (1979)
González, R.C., Woods, R.E.: Digital Image Processing, 3rd edn. Prentice Hall, Englewood Cliffs (2008)
Martín-Rodríguez, F.: Analysis Tools for Gray Level Histograms. In: Proceedings of SPPRA-2003, Signal Processing Pattern Recognition and Applications. Rhodes, Greece (2002), http://www.iasted.org
Proceedings of the IEEE (Special Isue on O.C.R.’s) 80(7) (1992)
Jain, A.K.: Fundamentals of Digital Image Processing. Prentice Hall, Englewood Cliffs (1989)
Blue, J.L., et al.: Evaluation of Pattern Classifiers for Fingerprint and OCR Applications. Pattern Recognition (Pergamon Press) 27(4), 485–501 (1994)
Vázquez-Fernández, E., et al.: Human Visual Perception as a Complementary Method for Digit Recognition. In: Proceedings of VIIP-2009 (Visualization, Imaging and Image Processing). Palma de Mallorca, Spain (2009), http://www.iasted.org
Corrêa Alegria, F., Cruz Serra, A.: Automatic Calibration of Analog and Digital Measuring Instruments Using Computer Vision. IEEE Transactions on Intrumentation and Measurement 49(1), 94–99 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Martín-Rodríguez, F., Vázquez-Fernández, E., Dacal-Nieto, Á., Formella, A., Álvarez-Valado, V., González-Jorge, H. (2010). Digital Instrumentation Calibration Using Computer Vision. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2010. Lecture Notes in Computer Science, vol 6112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13775-4_34
Download citation
DOI: https://doi.org/10.1007/978-3-642-13775-4_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13774-7
Online ISBN: 978-3-642-13775-4
eBook Packages: Computer ScienceComputer Science (R0)