International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.5, No.7, Jun. 2013

A Novel Container ISO Code Localization Using an Object Clustering Method with Opencv and Visual Studio Application

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Ronesh Sharma,Seong Ro Lee

Index Terms

Object clustering, Opencv, Container code localization, Image segmentation, Container recognition


An automatic container code recognition system is of a great importance to the logistic supply chain management. Techniques have been proposed and implemented for the ISO container code region identification and recognition, however those systems have limitations on the type of container images with illumination factor and marks present on the container due to handling in the mass environmental condition. Moreover the research is not limited for differentiating between different formats of code and color of code characters. In this paper firstly an object clustering method is proposed to localize each line of the container code region. Secondly, the localizing algorithm is implemented with opencv and visual studio to perform localization and then recognition. Thus for real time application, the implemented system has added advantage of being easily integrated with other web application to increase the efficiency of the supply chain management. The experimental results and the application demonstrate the effectiveness of the proposed system for practical use.

Cite This Paper

Ronesh Sharma,Seong Ro Lee,"A Novel Container ISO Code Localization Using an Object Clustering Method with Opencv and Visual Studio Application", IJIGSP, vol.5, no.7, pp.54-63, 2013.DOI: 10.5815/ijigsp.2013.07.08


[1]S. Kumano and K. Miyamoto, "Development of a Container Identification Mark Recognition System", Electronics and Communications in Japan, 87(12), 2004.

[2]R. 0hlander, K. Price, and D. R. Reedy, "Picture Segmentation Using A Recursive Region Splitting Method", Computer Graphics and Image Processing, 8: p. 313-333,1978.

[3]I. S. Igual, A. P. Jimenez, and G. A.Garica, Preprocessing and Recognition of Characters in Container Codes, 16th International Conference on Pattern Recognition, August 11-15, 2002.

[4]K. Koo and E. Cha, "A Novel Container ISO-Code Recognition Method using Texture Clustering with a Spatial Structure Window", International Journal of Advanced Science and Technology, 41, 2012.

[5]J. X. Wwan and Z. Zhou, The Research and Realization of Vehicle License Plate Character Segmentation and Recognition Technology, International Conference on Wavelet Analysis and Pattern Recognition, Portugal, July 10-14, 2010.

[6]K. K. Baek, W. Y. Woon, and Y. H. Kyu, An Intelligent System for Container Image Recognition Using ART2-Based Self-organizing Supervised Learning Algorithm, in Simulated Evolution and Learning, Springer Berlin Heidelberg, p. 897-904, 2006.

[7]S. H. Ong, N. C. Yeo, and K. H. Lee, Segmentation of color images using a two-stage self-organizing network, Image and Vision Computing, 20(4): p. 279-289, 2002.

[8]W. Wei, L. Zheng, and C. Mo, "An automated vision system for container-code recognition" Expert Systems with Applications, 39(3): p. 2842-2855, 2012.

[9]Wikipedia. Microsoft Visual Studio, Decmber 15; Available from:

[10]Wikipedia. opencv,Decmber 20; Available from:

[11]C. John and M. Lee, Automatic character recognition for moving and stationary vehicles and containers in real-life images, International Joint Conference on Neural Networks, Washington, DC, July 16, 2010.

[12]N. Murthy and K. swamy, "A Novel Method for Efficient Text Extraction from Real Time Images with Diversified Background using Haar Discrete Wavelet Transform and K-Means Clustering", International Journal of Computer Science, 8 ,2011.

[13]G. Bradski and A. Kaehler, M. Loukides, Computer Vision with Opencv Library, O'Reilly Media, Tokyo, 2008.

[14]M,Mori., ed. Character Recognition, Sciyo, Croatia ,2010.

[15]Wikipedia. ISO 6346. ,Decmber 18; Available from: