Skip to main content
Top

2019 | OriginalPaper | Chapter

Automatic Container Code Recognition System Based on Geometrical Clustering and Spatial Structure Template Matching

Authors : Lin Cao, Zhigang Gai, Enxiao Liu, Hao Gao, Hui Li, Lei Yang, Heng Li

Published in: Communications, Signal Processing, and Systems

Publisher: Springer Singapore

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

At present, at most ports the code of each container is registered manually, which is of a great potential safety hazard and inefficient. In this paper we present a container-code recognition system, which use the geometrical clustering of connected component extracted by MSER descriptor and spatial structure template matching for location and various CNN-classifiers for identification. Experiments confirmed the robustness and accurateness of the recognition algorithm on real images from ports.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Wu, W., Liu, Z., Chen, M., et al.: An automated vision system for container-code recognition. J. Expert Syst. Appl. 39, 2842–2855 (2012) Wu, W., Liu, Z., Chen, M., et al.: An automated vision system for container-code recognition. J. Expert Syst. Appl. 39, 2842–2855 (2012)
2.
go back to reference Kim, K.B., Woo, Y.W., Yang, H.K.: An intelligent system for container image recognition using ART2-based self-organizing supervised learning algorithm. In: International Conference Simulated Evolution and Learning, Hefei, China, pp. 897–904 (2006) Kim, K.B., Woo, Y.W., Yang, H.K.: An intelligent system for container image recognition using ART2-based self-organizing supervised learning algorithm. In: International Conference Simulated Evolution and Learning, Hefei, China, pp. 897–904 (2006)
3.
go back to reference Kyungmo, K., Hyunjun, P., Sangly, L., Euiyoung, C.: A text extraction in complex images using texture clustering method. In: KIICE, vol. 11. pp. 431–433(2007) Kyungmo, K., Hyunjun, P., Sangly, L., Euiyoung, C.: A text extraction in complex images using texture clustering method. In: KIICE, vol. 11. pp. 431–433(2007)
4.
go back to reference Igual, I.S., García, G.A., Jiménez, A.P.: Preprocessing and recognition of characters in container codes. In: 16th International Conference on Pattern Recognition, vol. 3, pp. 143–146 (2002) Igual, I.S., García, G.A., Jiménez, A.P.: Preprocessing and recognition of characters in container codes. In: 16th International Conference on Pattern Recognition, vol. 3, pp. 143–146 (2002)
5.
go back to reference Matas, J., Chum, O., Urban, M., et al.: Robust wide baseline stereo from maximally stable extremal regions. In: British Machine Vision Conference 2002. DBLP (2002) Matas, J., Chum, O., Urban, M., et al.: Robust wide baseline stereo from maximally stable extremal regions. In: British Machine Vision Conference 2002. DBLP (2002)
6.
go back to reference Koo, H.I., Kim, D.H.: Scene text detection via connected component clustering and nontext filtering. IEEE Trans. Image Proces. 22, 2296–2305 (2013) Koo, H.I., Kim, D.H.: Scene text detection via connected component clustering and nontext filtering. IEEE Trans. Image Proces. 22, 2296–2305 (2013)
7.
go back to reference Epshtein, B., Ofek, E., Wexler, Y.: Detecting text in natural scenes with stroke width transform. In: Computer Vision and Pattern Recognition, pp. 2963–2970. IEEE (2010) Epshtein, B., Ofek, E., Wexler, Y.: Detecting text in natural scenes with stroke width transform. In: Computer Vision and Pattern Recognition, pp. 2963–2970. IEEE (2010)
8.
go back to reference Neubeck, A., Gool, L.V.: Efficient non-maximum suppression. In: International Conference on Pattern Recognition, pp: 850–855. IEEE Computer Society (2006) Neubeck, A., Gool, L.V.: Efficient non-maximum suppression. In: International Conference on Pattern Recognition, pp: 850–855. IEEE Computer Society (2006)
9.
go back to reference Mitchell, T.M.: Machine Learning. McGraw-Hill Higher Education, New York (2001) Mitchell, T.M.: Machine Learning. McGraw-Hill Higher Education, New York (2001)
Metadata
Title
Automatic Container Code Recognition System Based on Geometrical Clustering and Spatial Structure Template Matching
Authors
Lin Cao
Zhigang Gai
Enxiao Liu
Hao Gao
Hui Li
Lei Yang
Heng Li
Copyright Year
2019
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-6571-2_268