• ETRI Journal
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• v.38 no.4
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• pp.767-775
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• 2016

Automatic container code recognition from a captured image is used for tracking and monitoring containers, but often fails when the code is not captured clearly. In this paper, we increase the accuracy of container code recognition using multiple views. A character-level integration method combines recognized codes from different single views to generate a new code. A decision-level integration selects the most probable results from the codes from single views and the new integrated code. The experiment confirmed that the proposed integration works successfully. The recognition from single views achieved an accuracy of around 70% for the test images collected on a working pier, whereas the proposed integration method showed an accuracy of 96%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1478-1489
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• 2006

This paper describes system to extract ISO codes in container image. A container ISO code recognition system for real-time processing is made of 5 core parts which are container ISO code detection and image acquisition, ISO code region extraction, individual character extraction, character recognition and database. Among them, the accuracy of ISO code extraction can affect significantly the accuracy of system recognition rate, and also the more exact extraction of ISO code is required in various weather and environment conditions. The proposed system produces binary of the ISO code's template lesions using an adaptive thresholding, extracts candidate regions containing distribution of ISO code, and recognizes ISO codes as detecting a final region through the verifications by using character distribution characteristics of ISO code among the extracted candidates. Experimental results reveal that ISO codes can be efficiently extracted by the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1462-1470
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• 2015

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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.721-723
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• 2007

Recently, the size and location of the acquired container image while the container is loading and unloading in Harbors is not fixed. And it is difficult to get a good image for recognition because of the variation of external environment as those the size of container and where the yard-tractor stop is. In this paper, we estimate where the container ISO-code set is using Top-hat transform from realtime images and get an image to recognize container ISO-code using PAN/TILT/ZOOM camera. We extract the container ISO-code using Top-hat transform and Histogram projection. After binarization, we extract each character from complex background using labeling. We use BP(Backpropagation Network) to recognize extracted characters.

• Journal of Navigation and Port Research
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• v.31 no.9
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• pp.771-778
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• 2007

A container terminal gate is not only an entrance of containers, but also the first input point of containers' information. Therefore, to achieve the accuracy of container information, there are various containers' numbers recognition methods used. Gate productivity can significantly vary depending upon those recognition methods. Recently, RFID which is one of the u-IT businesses run by the Korean government is under consideration for application to the gate as an automatic system. If RFID is used, it is expected to have both the qualitative benefits through avoiding defects of other systems and the quantitative benefits by improving productivity. Hence, this study aims to provide some insight on the benefits of RFID, and to compare productivity of the existing gate system with the RFID gate system based on computer simulation.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.19-26
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• 2022

This paper presents a pre-processing method to facilitate the container's BIC-code recognition. We propose a network that can find ROI(Region Of Interests) containing a BIC-code region and estimate a homography matrix for warping. Taking the structure of STN(Spatial Transformer Networks), the proposed network consists of next 3 steps, ROI detection, homography matrix estimation, and warping using the homography estimated in the previous step. It contributes to improving the accuracy of BIC-code recognition by estimating ROI and matrix using the proposed network and correcting perspective distortion of ROI using the estimated matrix. For performance evaluation, five evaluators evaluated the output image as a perfect score of 5 and received an average of 4.25 points, and when visually checked, 224 out of 312 photos are accurately and perfectly corrected, containing ROI.

• Journal of Navigation and Port Research
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• v.29 no.9
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• pp.789-793
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• 2005

The container terminals in Korea usually adopts both the bar code and the image recognition systems at the gate complex to capture necessary information on containers passing through the gate. With the rapid advancement of Information Technology(IT) these systems, however, seem to make the user not satisfied due to the inherent limitations such as the long process time taken, low rate of recognition etc., This paper, therefore, examines the adoption of Radio Frequency Identification (RFID) technology to container terminals, and tried to get some implication for the way to improve the productivity of the terminal. The results imply that some improvement in the gate and storage yard operation is feasible by the benefit of using the information of vehicles and containers collected in advance by RFID technology.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.29-30
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• 2014

본 논문에서는 컨테이너 BIC-code 자동인식 시스템의 전 처리 과정으로서 다중 임계값을 이용한 BIC-code 영역 추출 방법을 제안한다. 기후요소, 빛, 카메라 위치, 컨테이너의 색과 같은 다양한 요인으로 인해 고정된 임계값을 사용할 수 없다. 따라서 각 영상에 대해 다양한 임계값으로 실험하여 컨테이너 BIC-code 인식에 가장 우수한 임계값을 결정하여 영상을 이진화한다. 다음으로, 가장 우수한 임계값으로 이진화 한 영상에 대하여 레이블링, 닫힘 연산을 통해 BIC-code의 가로, 세로 여부를 판단하게 된다. 또한 레이블링 된 각 영역을 판단하여 잡음을 제거하고, 개별 code를 분리한다. 제안된 방법에 대한 실험결과 성공적인 코드 영역 분리가 가능함을 확인할 수 있었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.278-287
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• 2013

Modern information technologies continue to provide industries with new and improved methods. With the rapid development of Machine to Machine (M2M) communication, a smart container supply chain management is formed based on high performance sensors, computer vision, Global Positioning System (GPS) satellites, and Globle System for Mobile (GSM) communication. Existing supply chain management has limitation to real time container tracking. This paper focuses on the studies and implementation of real time container chain management with the development of the container identification system and automatic alert system for interrupts and for normal periodical alerts. The concept and methods of smart container modeling are introduced together with the structure explained prior to the implementation of smart container tracking alert system. Firstly, the paper introduces the container code identification and recognition algorithm implemented in visual studio 2010 with Opencv (computer vision library) and Tesseract (OCR engine) for real time operation. Secondly it discusses the current automatic alert system provided for real time container tracking and the limitations of those systems. Finally the paper summarizes the challenges and the possibilities for the future work for real time container tracking solutions with the ubiquitous mobile and satellite network together with the high performance sensors and computer vision. All of those components combine to provide an excellent delivery of supply chain management with outstanding operation and security.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.977-980
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• 2007

본 논문은 인식된 컨테이너 식별자 문자열과 컨테이너 작업리스트를 비교하여 작업리스트와 인식된 컨테이너 식별자 문자열을 매칭하는 효율적인 방법을 소개하고자 한다. Dynamic Time Warping 기법을 이용하여 오인식되거나 인식이 되지 않은 문자에 대하여 오독률을 최소화할 수 있는 효율적인 방법을 제안한다. 기존의 문자열 비교방식에 비하여 제안하는 방법을 사용하였을 경우 더 나은 성능을 보였다.