• Resources Recycling
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• v.17 no.6
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• pp.43-49
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• 2008

In this study, a scrap sorting system using a color recognition method has been developed to automatically sort out specified materials from a mixture, and its application as been examined in the separation of Cu and other non-ferrous metal parts from a mixture of iron scraps. The system is composed of three parts; measuring, conveying and ejecting parts. The color of scrap surface is recognized by the measuring part consisting of a line-scan camera, light sources and a frame grabber. The recognition is program-controlled by a image processing algorithms, and thus only the scrap part of designated color is separated by the use of air nozzles. In addition, the light system is designed to meet a high speed of sorting process with a frequency-variable inverter and the air nozzled ejectors are to be operated by an I/O interface communication with a hardware controller. In the functional tests of the system, its efficiency in the recognition of Cu scraps from its mixture with Fe ones reaches to more than 90%, and that in the separation more than 80% at a conveying speed of 25 m/min. Therefore, it is expected that the system can be commercialized in the industry of shredder makers if a high efficiency ejecting system is realized.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.4
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• pp.517-522
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• 2011

Conventional projection welding systems suffer from lots of defective products caused by manual handling. In this paper, we introduce a projection welding system that performs automatic identification, welding and counting of components and products. The proposed system checks the existence and identifies placement of components to be welded by a vision camera. After welding of the components, it automatically updates product counts and dressing items. We show that the proposed welding system can reduce the defect rate and improve the productivity through experimental test with a existing system.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.35-43
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• 2004

In this paper, we proposed a vehicle recognition and electronic toll collection system with detection and classification of vehicle identification mark and emblem as well as recognition of vehicle license plate to unman toll fee collection system or incoming/outcoming vehicles to an institution. In the proposed algorithm, we first process pre-processing step such as noise reduction and thinning from the rear side input image of vehicle and detect vehicle mark, emblem and license plate region using intensity variation informations, template masking and labeling operation. And then, we classify the detected vehicle features regions into vehicle mark and emblem as well as recognize characters and numbers of vehicle license plate using hybrid and seven segment pattern vector. To show the efficiency of the proposed algorithm, we tested it on real vehicle images of implemented vehicle recognition system in highway toll gate and found that the proposed method shows good feature detection/classification performance regardless of irregular environment conditions as well as noise, size, and location of vehicles. And also, the proposed algorithm may be utilized for catching criminal vehicles, unmanned toll collection system, and unmanned checking incoming/outcoming vehicles to an institution.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.131-134
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• 1998

본 논문에서는 전자 개인 비서 시스템(PEAS)의 일부인 일정관리 시스템을 화자인식 기술을 적용하여 구현하였다. 본 시스템은 음성을 패스워드로 개인을 확인하여 각 개인의 일정을 관리해 주는 것으로 보안성과 함께 사용자에게 편의성을 제공한다. 사용자 등록을 자유롭게 하였으며 인식에서는 계산 시간 등을 고려하여 DTW 알고리즘에서 얻을 수 있는 경로정보를 이용해 하나의 참조패턴을 구성하도록 하였다. 또한 시간 흐름에 따라 인식율 저하를 방지하기 위해 실험결과에 따라 일정기간 뒤에 자동으로 참조패턴이 갱신되도록 하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.5 no.3 s.11
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• pp.24-28
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• 2006

This paper proposed design and implementation of automation system that recognize device module boards automatically that are connected on main control board. The system of this paper is divided to main board and device module boards, and the main board is designed a board by slot structure. The slot structure is possible a extension for upgrade and addition of board ability. Besides, it is easier a establishment and disjointing because it recognizes automatically a device board. The proposed system in this paper compares with K10S1 PLC. The result shows an advantage of extensibility and ability, and it is reduced expense and period for development.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.185-193
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• 2011

There is no exact standard of detecting pulmonary tuberculosis(TB) in digital image of simple chest radiography. In this study, I experimented on the principal components analysis(PCA) algorithm in the past and suggested six other parameters as identification of TB lesions. The purpose of this study was to develop and test computer aided diagnosis(detection) method for the detection and measurement of pulmonary abnormalities on digital chest radiography. It showed comparatively low recognition diagnosis rate using PCA method, however, six kinds of texture features parameters algorithm showed similar or higher diagnosis rates of pulmonary disease than that of the clinical radiologists. Proposed algorithms using computer-aided of texture analysis can distinguish between areas of abnormality in the chest digital images, differentiate lesions having pulmonary disease. The method could be useful tool for classifying and measuring chest lesions, it would play a major role in radiologist's diagnosis of disease so as to help in pre-reading diagnosis and prevention of pulmonary tuberculosis.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.697-698
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• 2021

본 논문에서는 시각 장애우의 식품 안전성 증진을 위해 광학 문자 인식 (optical character recognition, OCR) 및 실시간 객체 인식 (you only look once, YOLO) 알고리즘에 기반한 식품의 유통기한 자동 알림 시스템을 제안한다. 제안하는 시스템은 1) 스마트폰 카메라를 통해 실시간으로 입력되는 영상에서 YOLO 알고리즘을 활용하여 유통기한으로 예측되는 이미지 영역을 검출하고, 2) 검출된 영역에서 OCR 알고리즘을 활용하여 유통기한 데이터를 추출하며, 3) 최종 추출된 유통기한 데이터를 음성으로 변환하여 시각 장애우에게 전달한다. 개발된 시스템은 유통기한 정보를 추출해서 사용자에게 전달하기까지 평균 약 7초 이내의 빠른 응답 속도를 보였으며, 62.8%의 객체 인식 정확도와 93.6%의 문자 인식 정확도를 보였다. 이러한 결과들은 제안하는 시스템을 시각 장애우들이 실용적으로 활용할 수 있다는 가능성을 보여준다.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.43-54
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• 2008

In this paper, we implement an automatic entity information management system for smart refrigerator using RFID technology in which objects containing electronic tags are automatically identified using radio wave. Unlike current "smart" refrigerators, the system presented in this paper implements smart tag information acquisition mechanism and real-time information management system to provide various information on entities in refrigerators to local and remote users. As the first step, this paper analyzes the requirements for smart refrigerator system based on the RFID and suggests design considerations. Based on the analysis, we propose and implement an efficient tag location tracking method based on antenna transfer method and an intelligent tag information management system based on embedded database and web server. We also provide a wide range of experimental results on the number of tags identified at a time and the tag recognition ratio according to the RFID antenna transfer speed and the angle between tag reader and tags.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.1-8
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• 2001

In this paper, we proposed the automatical recognition algorithm of bar-code using a vision system, which can be used in the industrial application(code 93). The proposed algorithm extracts the pixels which consist of the bar-code modules unrelated to rotation, then that obtains the elements which consist of bars and spaces. After the obtained elements are divided by nine group, the value of bar-code is recognized. The performance of proposed algorithm is verified through the simulation. The proposed one has good performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.823-825
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• 2014

감시 카메라 환경에서 자동으로 그룹 행동을 인식하는 기술이 최근 많은 관심을 받고 있다. 본 논문에서 제안하는 그룹 해동 인식 시스템은 다른 추가 정보 없이 비디오 프레임만을 인풋으로 받아들여, 자동으로 보행자 탐지, 추적, 행동 인식까지 모두 포괄하는 시스템이다. 시공간 모션 패턴을 만들고 연결 요소들로 모델링 한 뒤 Hidden Markov Model (HMM)을 이용해 그룹 행동을 인식한다. 실험 결과, 기본 논문과 비교하였을 때, 비슷한 인식률을 보이면서 수행 시간을 약 25 배 정도로 획기적으로 단축하였다.