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http://dx.doi.org/10.6109/jkiice.2015.19.6.1462

Container BIC-code region extraction and recognition method using multiple thresholding  

Song, Jae-wook (Graduate School of Electrical Engineering and Computer Science, Chungbuk University)
Jung, Na-ra (Graduate School of Electrical Engineering and Computer Science, Chungbuk University)
Kang, Hyun-soo (Graduate School of Electrical Engineering and Computer Science, Chungbuk University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.19, no.6, 2015 , pp. 1462-1470 More about this Journal
Abstract
The container BIC-code is a transport protocol for convenience in international shipping and combined transport environment. It is an identification code of a marine transport container which displays a wide variety of information including country's code. Recently, transportation through aircrafts and ships continues to rise. Thus fast and accurate processes are required in the ports to manage transportation. Accordingly, in this paper, we propose a BIC-code region extraction and recognition method using multiple thresholds. In the code recognition, applying a fixed threshold is not reasonable due to a variety of illumination conditions caused by change of weather, lightening, camera position, color of the container and so on. Thus, the proposed method selects the best recognition result at the final stage after applying multiple thresholds to recognition. For each threshold, we performs binarization, labeling, BIC-code pattern decision (horizontal or vertical pattern) by morphological close operation, and character separation from the BIC-code. Then, each characters is recognized by template matching. Finally we measure recognition confidence scores for all the thresholds and choose the best one. Experimental results show that the proposed method yields accurate recognition for the container BIC-code with robustness to illumination change.
Keywords
BIC-code; threshold; template Matching; recognition;
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Times Cited By KSCI : 1  (Citation Analysis)
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