• Journal of Korea Multimedia Society
• /
• v.2 no.4
• /
• pp.390-399
• /
• 1999

Extracting the character region(container identifier) in the image of a shipping container is one of the key factors in a system for identifying a shipping container automatically To improve the performance of the automatic recognition system for identifying a shipping container, thus a method partitioning the character region more correctly and efficiently is needed. In this paper, an efficient method is proposed to extract only the character region in the image of a shipping container. The proposed method removes noises that are not possibly related to the character using morphological operation, then the image is binarized using the threshold value that is determined from the image obtained previous step. Finally individual character area is extracted from the binary image. Also experiments are conducted to verify the efficiency of the proposed method. The results show that the proposed method partitions the character region correctly from container images.

• Journal of Korea Multimedia Society
• /
• v.16 no.5
• /
• pp.549-557
• /
• 2013

This paper proposes a method using the multiple threshold regions in the image preprocessing procedure for container identifier recognition system. The multiple threshold regions are set by considering the container image characteristics and used as the candidates for the final one, The image is transformed to black and white images using these threshold regions, then labeling, panelling and panels merging are executed for each candidate, respectively. Finally the best threshold region is selected through this procedure and the character region can be extracted. Applying the similar method the noises are removed and the characters of identifier are segmented from the extracted region. In the experiments with 162 different images the success rates for extracting of the character region and segmenting the characters are 99.04% and 98.09%, respectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.12a
• /
• pp.365-369
• /
• 2002

퍼지 ART 알고리즘에서 경계 변수는 패턴들을 클러스터링하는데 있어서 반지름 값이 되며 임의의 패턴과 저장된 패턴과의 불일치(mismatch) 허용도를 결정한다. 이 경계 변수가 크면 입력 벡터와 기대 벡터 사이에 약간의 차이가 있어도 새로운 카테고리(category)로 분류하게 핀다. 반대로 경계 변수가 작으면 입력 벡터와 기대 벡터 사이에 많은 차이가 있더라도 유사성이 인정되어 입력 벡터들을 대략적으로 분류한다. 따라서 영상 인식에 적용하기 위해서는 경험적으로 경계 변수를 설정해야 단점이 있다. 그리고 연결 가중치를 조정하는 과정에서 저장된 패턴들의 정보들이 손실되는 경우가 발생하여 인식율을 저하시킨다. 된 논문에서는 퍼지 ART 알고리즘의 문제점을 개선하기 위하여 퍼지 논리 접속 연산자를 이용하여 경계 변수를 동적으로 조정하고 저장 패턴들과 학습 패턴간의 실제적인 왜곡 정도를 충분히 고려하여 승자 노드로 선택된 빈도수를 가중치 조정에 적용한 개선된 퍼지 ART 알고리즘을 제안하였다. 제안된 방법의 성능을 확인하기 위해서 실제 운송 컨테이너 영상들을 대상으로 실험한 결과, 기존의 ART2 알고리즘이나 퍼지 ART 알고리즘보다 클러스터의 수가 적게 생성되었고 인식 성능도 기존의 방법들보다 우수한 성능이 있음을 확인하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 1998.10a
• /
• pp.137-141
• /
• 1998

Todays the efficient management of container has not been realized in container terminal, because of the excessive quantity of container transported and manual system. For the efficient and automated management of container in terminal, the automated container identifier recognition system in terminal is a significant problem. However, the identifier recognition rate is decreased owing to the difficulty of image preprocessing caused the refraction of container surface, the change of weather and the damaged identifier characters. Therefore, this paper proposes more accurate system for container identifier recognition as suggestion of Line-Scan Proper Region Detect for stronger preprocessing against external noisy element and Moment Back-Propagation Neural Network to recognize identifier.

• Journal of Korean Port Research
• /
• v.12 no.2
• /
• pp.225-232
• /
• 1998

Todays, the efficient management of container has not been realized in container terminal, because of the excessive quantity of container transported and manual system. For the efficient and automated management of container in terminal, the automated container identifier recognition system in terminal is a significant problem. However, the identifier recognition rate is decreased owing to the difficulty of image preprocessing caused the refraction of container surface, the change of weather and the damaged identifier characters. Therefore, this paper proposes more accurate system for container identifier recognition as suggestion of LSPRD(Line-Scan Proper Region Detection) for stronger preprocessing against external noisy element and MBP(Momentum Back-Propagation) neural network to recognize the identifier.

• Journal of Korean Port Research
• /
• v.13 no.2
• /
• pp.303-312
• /
• 1999

The automated gate operating system is developed in this paper that controls the information of container at gate in the ACT. This system can be divided into three parts and consists of container identifier recognition car plate recognition container deformation perception. We linked each system and organized efficient gate operating system. To recognize container identifier the preprocess using LSPRD(Line Scan Proper Region Detection)is performed and the identifier is recognized by using neural network MBP When car plate is recognized only car image is extracted by using color information of car and hough transform. In the port of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container. Thirdly edge is fitted into line segment so that container deformation is perceived. As a results of the experiment with this algorithm superior rate of identifier recognition is shown and the car plate recognition system and container deformation perception that are applied in real-time are developed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.5C
• /
• pp.486-492
• /
• 2003

The vigilance threshold of conventional fuzzy ART algorithm decide whether to permit the mismatch between any input pattern and stored pattern. If the vigilance threshold was large, despite of little difference among input and stored patterns, the input pattern may be classified to new category. On the other hand, if the vigilance threshold was small, the similarity between two patterns may be accepted in spite of lots of difference and the input pattern are classified to category of the stored pattern. Therefore, the vigilance threshold for the image recognition must be experientially set for the good result. Moreover, it may occur in the fuzzy ART algorithm that the information of stored patterns is lost in the weight-adjusting process and the rate of pattern recognition is dropped. In this paper, I proposed the enhanced fuzzy ART algorithm that supports the dynamical setting of the vigilance threshold using the generalized intersection operator of fuzzy logic and the weight value being adaptively set in proportional to the current weight change and the previous weight by reflecting the frequency of the selection of winner node. For the performance evaluation of the proposed method, we applied to the recognition of container identifiers from shipping container images. The experiment showed that the proposed method produced fewer clusters than conventional ART2 and fuzzy ART algorithm. and had tile higher recognition rate.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.9
• /
• pp.33-38
• /
• 2014

The FCM based hybrid RBF network is a heterogeneous learning network model that applies FCM algorithm between input and middle layer and applies Max_Min algorithm between middle layer and output. The Max-Min neural network uses winner nodes of the middle layer as input but shows inefficient learning in performance when the input vector consists of too many patterns. To overcome this problem, we propose a dynamic learning rate control based on fuzzy logic. The proposed method first classifies accurate/inaccurate class with respect to the difference between target value and output value with threshold and then fuzzy membership function and fuzzy decision logic is designed to control the learning rate dynamically. We apply this proposed RBF network to the character recognition problem and the efficacy of the proposed method is verified in the experiment.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2005.05a
• /
• pp.36-43
• /
• 2005

RFID(Radio Frequency IDentification: 라디오 주파수 인식)란 라디오 주파수를 활용해서 무선으로 사물을 인식하는 것을 의미한다. RFID 기술을 구성하는 기본 요소는 태그, 안테나, 리더 등이다. 본 연구에서는 이러한 RFID 기술의 기본 요소와 더불어 인식된 사물의 정보를 광범위하게 구축되어 있는 유${\cdot}$무선 네트워크와 연결하여 활용할 수 있는 모든 기술을 RFID 기술로 정의하였다. 비록 최근에 RFID 기술이 여러 분야에서 큰 이슈로 떠오르고 있지만, 실제 RFID 기술은 오래전인 2차 세계대전에 영국군의 자국 전투기 식별을 위해 이미 활용되고 있었다. 그러나 그 당시에는 RFID 기술의 구성요소인 태그나 리더의 값이 고가였기 때문에 특정분야에 한해 RFID 기술을 적용할 수 있었다. 그 이후에 1990년대에 이르러 RFID 기술은 가축관리, 컨테이너관리, IC 카드 등 점차 다른 분야로 적용이 확대되기 시작했다. 특히 반도체 기술의 발전이 급속도로 이루어진 1990년대 말을 기점으로 RFID 기술에 대한 연구가 활발히 이루어져, 현재에는 SCM(Supply Chain Management), 국방, 의료, 교통, 환경, 동물관리, 홈 네트워크 등 다양한 분야에 적용이 가능한 기술로 평가되고 있다. 특히, SCM에 있어서 RFID 기술 도입은 큰 파급효과가 예상되고 있다. SCM을 구성하는 기업들은 RFID 기술 도입을 통해 제품의 가시성(visibility)과 추적성(traceability)을 확보할 수 있게 된다. 기업들은 자신의 제품이 현재 어디에 있으며 어떠한 경로를 통해 그 자리에 이르렀는지를 실시간(real time)으로 확인 가능하게 된다. 미국의 월마트사(社) 와 영국의 메트로사(社) 같은 선진 유통 기업들은 실증연구를 통해 RFID 기술 도입이 비용 절감과 함께 고객 서비스 향상을 도모할 것이라는 결론을 내린 바 있다. 또한 현제 초기단계이기는 하지만 실제 RFID 기술을 도입하여 운영 중에 있다. 국내에서도 정부주도 하에 RFID 기술에 대한 연구가 활발하게 이루어지고 있으며, 지난 2004년에 유통 물류 분야의 1차 시범사업을 완료하였다. 그러나, 이러한 국내${\cdot}$외의 적극적인 도입 움직임에도 불구하고 국내에서는 아직 RFID기술 도입이 SCM(Supply Chain Management)에 있어서 구체적으로 어떠한 영향을 미치는가에 대한 연구가 거의 이루어지지 못하고 있는 실정이다. 특히 RFID 기술 도입 의사결정자에게 제공될 수 있는 정량적인 ROI 분석 모형에 관한 연구는 시급한 과제로 떠오르고 있다. 따라서 본 연구에서는 SCM 차원에서 RFID 기술 도입에 따른 ROI 분석 모형을 제시하고 적용해 보고자 한다.

• The Journal of the Korea Contents Association
• /
• v.17 no.7
• /
• pp.276-282
• /
• 2017

Password-based authentication is vulnerable because of its low cost and convenience, but it is still widely used. In order to increase the security of the password-based user authentication method, the password is changed frequently, and it is recommended to use a combination of numbers, alphabets and special characters when generating the password. However, it is difficult for users to remember passwords that are difficult to create and it is not easy to change passwords periodically. Therefore, in this paper, we implemented a user authentication system that does not require a password by using the USB memory that is commonly used. Authentication data used for authentication is protected by USB data stored in USB memory using USB device information to improve security. Also, the authentication data is one-time and reusable.Based on this, it is possible to have the same security as the password authentication system and the security level such as certificate or fingerprint recognition.