• 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.

• Journal of Digital Contents Society
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• v.12 no.1
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• pp.57-67
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• 2011

Recently, an interest in a mobile search is increasing according to the growing propagation of smart phones. However, a keypad, which is not appropriate for mobile environment, is the only input media for the mobile search. As an alternative, voice emerged as a new media for the mobile search, but this also has weaknesses. Thus, in the paper, we propose a mobile content called Orthros for searching the Internet using images as an input. Orthros extracts texts from images, and then inserts the texts to public search engines as a keyword. Also, Orthros can repeat searching with the extracted texts by storing result URL to internal databases. As an experiment, we analyze properties of recognizable images and present the implementation method in details.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.199-200
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• 2021

최근 어린이 보호구역 내에서의 운전자의 부주의로 사망 혹은 상해 사고를 일으킨 가해자를 가중 처벌하는 내용의 '민식이법'이 발의됨에 따라 많은 운전자들이 보호구역을 주행할 때 많은 부담감을 느끼며, 이에 대한 운전자의 부담감과 사고 피해를 최소화할 수 있는 시스템이 필요하다. 본 논문에서는 OpenCV 영상인식기술과 OCR 문자인식기술인 Tesseract를 이용해 노약자 보호구역 표지판을 인식하여 법정 제한속도를 준수하며 갑작스러운 장애물 등장 시 급정거하여 사고피해를 최소화하고, 또한, 사용자에게 알람 메시지를 전송하는 시스템을 제안한다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.595-603
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• 2015

With the advances of the big-data process technology, acquiring the real-time information from the massive image data taken by a mobile device inside a vehicle will be possible in the near future. Among the information that can be found around the vehicle, the route information is needed for safe driving. In this study, the automatic extraction of route information from the road sign imagery was dealt with. The scope of the route information in this study included the route number, route type, and their relationship with the driving direction. For the recognition of the route number, the modified Tesseract OCR (Optical Character Recognition) engine was used after extracting the rectangular-road-sign area with the Freeman chain code tracing algorithm. The route types (expressway, highway, rural highway, and municipal road) are recognized using the proposed algorithms, which are acquired from colour space analysis. Those road signs provide information about the route number as well as the roads that may be encountered along the way. In this study, such information was called “OTW (on the way)” or “TTW (to the way)” which between the two should be indicated is determined using direction information. Finally, the route number is matched with the direction information. Experiments are carried out with the road sign imagery taken inside a car. As a result, route numbers, route number type, OTW or TTW are successfully recognized, however some errors occurred in the process of matching TTW number with the direction.