• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.285-288
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• 2009

동영상에서 물체를 추적하기 위한 많은 방법들은 각 방법마다 다양한 요소들을 이용한다. 하지만 다양한 요소들은 그 관계를 명확히 나타낼 수 없다. 본 논문에서는 동영상에서 물체 추적을 위해 시각적 기본 요소의 동일성을 나타내고 설명하기 위한 방법을 제안한다. 시각적 기본 요소란 이미지에서 얻을 수 있는 순수한 시각적 기본 요소들인 색상, 명암, 윤곽선 정보를 말하며 이 정보를 이용하여 연속된 프레임을 비교해 동일한 물체인지를 판단한다. 그리하여 판단된 정보를 가지고 추적에 사용되는 요소들의 지속적인 갱신을 통해 대상을 모델 없이 추적하고 인식 과정에 대하여 제어가 가능하도록 한다.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.171-178
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• 2010

The surveillance system in general, has been sufficiently studied in the field of wireless semiconductor using basic sensors and its study of image surveillance system mainly using camera as a sensor has especially been fully implemented. In this paper, we propose 'Intelligent Image Detection System' used by image object identification technique based on the result analysis of various researches. This 'Intelligent Image Detection System' can easily trace and judge before and after a particular incident and ensure affirmative evidence and numerous relative information. Therefore, the 'Intelligent Image Detection System' proposed in this paper can be effectively used in the lived society such as traffic management, disaster alarm system and etc.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.477-486
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• 2016

This paper presents the area classification, identification, and tracking for multiple moving objects with the similar colors. To do this, first, we use the GMM(Gaussian Mixture Model)-based background modeling method to detect the moving objects. Second, we propose the use of the binary and morphology of image in order to eliminate the shadow and noise in case of detection of the moving object. Third, we recognize ROI(region of interest) of the moving object through labeling method. And, we propose the area classification method to remove the background from the detected moving objects and the novel method for identifying the classified moving area. Also, we propose the method for tracking the identified moving object using Kalman filter. To the end, we propose the effective tracking method when detecting the multiple objects with the similar colors. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.91-98
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• 2016

Detection and classification of underwater objects in sonar imagery are challenging problems. This paper proposes a system that detects and identifies underwater objects at the sea floor level using a sonar image and image processing techniques. The identification process of underwater objects consists of two steps; detection of candidate regions and identification of underwater objects. The candidate regions of underwater objects are extracted by image registration through the detection of common feature points between the reference background image and the current scanning image. And then, underwater objects are identified as the closest pattern within the database using eigenvectors and eigenvalues as features. The proposed system is expected to be used in efficient securement of Q route in vessel navigation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.293-300
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• 2018

We propose a moving object extraction and tracking method for improvement of animal identification and tracking technology. First, we propose a method of merging separated moving objects into a moving object by using FCM (Fuzzy C-Means) clustering algorithm to solve the problem of moving object loss caused by moving object extraction process. In addition, we propose a method of extracting data from a moving object and a method of counting moving objects to determine the number of clusters in order to satisfy the conditions for performing FCM clustering algorithm. Then, we propose a method to continuously track merged moving objects. In the proposed method, color histograms are extracted from feature information of each moving object, and the histograms are continuously accumulated so as not to react sensitively to noise or changes, and the average is obtained and stored. Thereafter, when a plurality of moving objects are overlapped and separated, the stored color histogram is compared with each other to correctly recognize each moving object. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.131-147
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• 2020

RFID (Radio Frequency Identification) identifies a specific object by radio signals. As the tag provides a unique ID for the purpose of identification, RFID technology effectively solves the ambiguity and occlusion problem that challenges the laser or camera-based approach. This paper proposes an approach to track a moving object based on the integration of RFID and laser ranging information using a particle filter. To be precise, we split laser scan points into different clusters which contain the potential moving objects and calculate the radial velocity of each cluster. The velocity information is compared with the radial velocity estimated from RFID phase difference. In order to achieve the positioning of the moving object, we select a number of K best matching clusters to update the weights of the particle filter. To further improve the positioning accuracy, we incorporate RFID signal strength information into the particle filter using a pre-trained sensor model. The proposed approach is tested on a SCITOS service robot under different types of tags and various human velocities. The results show that fusion of signal strength and laser ranging information has significantly increased the positioning accuracy when compared to radial velocity matching-based or signal strength-based approaches. The proposed approach provides a solution for human machine interaction and object tracking, which has potential applications in many fields for example supermarkets, libraries, shopping malls, and exhibitions.

• Review of Korean Society for Internet Information
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• v.16 no.1
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• pp.49-53
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• 2015

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.171-179
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• 2013

During 19th general election the customized LBSNS(Location Based SNS) application for some candidates of the National Assembly planned and developed based on the object identification, ePosition, comprising the candidate's name have been applied for an election campaign. The approval rating change before and after 19th election campaign period for each candidate was quantitatively studied how it would be affected by the candidate custom LBSNS application. Only 3 out of 24 candidates in 6 local electorates in the Daejon Metropolitan City have adopted the customized LBSNS application and the rest 21 candidates have not, whose approval rating change before and after an election campaign has been analyzed comparatively candidate by candidate. The approval rating for 3 candidates adopting LBSNS application went up by 12.6%, 11.4%, 11.2% respectively, but those for the rest 21 candidates all changed within 3%.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.11-13
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• 2010

Combined with the indeterminate boundaries of spatial objects, n:m correspondences makes an object-based matching be a complex problem. In this study, we model the boundary of a polygon object with fuzzy model and describe their overlapping relations as a weighted bipartite graph. Then corresponding pairs including 1:0, 1:1, 1:n and n:m relations are identified using a spectral singular value decomposition.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10b
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• pp.1261-1266
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• 2000

In the impact echo method, a stress pulse is introduced into an object at on accessible surface by a transmitter. The pulse propagates into the test object and is reflected by flaws or interfaces. In this paper, void and crack locations of concrete specimens were detected using impact echo method. In their modal identification procedures, the double least squares solution for Ibrahim Time Domain technique was used.