• 대한임베디드공학회논문지
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• 제17권6호
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• pp.337-346
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• 2022

This paper addresses the problem of vision-based ear loops ansd attachment inspection in mask production lines. This paper focuses on connections with ear loops and mask filter by an efficient combined approach. The proposed method used a template matching, shape detection and summation of histogram with preprocessing. We had a parameter for detecting defects heuristically. If the shape vertices are lower than the parameters our proposed method will find defective mask automatically. After finding normal masks in mask ear loops attachment status inspection algorithm our proposed method conducts attachment amount inspection. Our experimental results showed that the precision is 1 and the recall is 0.99 in the mask attachment status inspection and attachment amount inspection.

• 한국컴퓨터정보학회논문지
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• 제26권6호
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• pp.47-53
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• 2021

본 논문에서는 단일 팬 방식 홀로그램 디스플레이의 제한된 시야각 문제점을 개선하기 위한 멀티비전 기반 홀로그램 디스플레이를 제안한다. 기존 단일 팬 방식의 디스플레이는 시야각이 좁고 팬의 길이가 길어짐으로 인한 낮은 해상도의 문제점을 가진다. 또한, SD 카드 사용으로 인한 데이터 변경의 어려움을 Wi-Fi 방식으로 데이터를 송신하기 위한 전용 앱을 구현하고자 한다. 본 논문에서는 3개의 REG LED 팬으로 구성된 디스플레이를 설계하고 구현하였다. 앱을 이용한 영상송신 결과, 광고 및 시연 등의 상업적 용도로 사용할 수 있음을 확인하였다. 본 연구의 결과는 멀티비전 홀로그램의 대중화에 많은 도움이 될 것으로 사료된다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2012년도 한국컴퓨터종합학술대회논문집 Vol.39 No.1(D)
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• pp.61-63
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• 2012

본 논문에서는 다중 플랫폼을 지원하는 증강현실 콘텐츠 저작 시스템을 소개한다. 소개하는 저작 시스템은 일반 PC 환경과 모바일 환경에서 구현되었으며 같은 오픈 소스 엔진을 사용하여 상호 호환이 가능하다. 또한 시스템에 콘텐츠 파일의 저장 및 전송을 담당할 서버를 함께 구성하여 사용자의 증강현실 콘텐츠 저작에 대한 파일 접근성을 높였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 추계학술대회 논문집
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• pp.603-604
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• 2006

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.780-785
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• 1992

We present a multi-sensor fusion method in positioning control of a robot by using fuzzy logic. In general, the vision sensor is used in the gross motion control and the force/torque sensor is used in the fine motion control. We construct a fuzzy logic controller to combine the vision sensor data and the force/torque sensor data. Also, we apply the fuzzy logic controller to the peg-in-hole process. Simulation results uphold the theoretical results.

• 전기학회논문지
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• 제63권11호
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• pp.1551-1558
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• 2014

We propose a multi-rate sensor fusion of vision and radar using Kalman filter to solve problems of asynchronized and multi-rate sampling periods in object vehicle tracking. A model based prediction of object vehicles is performed with a decentralized multi-rate Kalman filter for each sensor (vision and radar sensors.) To obtain the improvement in the performance of position prediction, different weighting is applied to each sensor's predicted object position from the multi-rate Kalman filter. The proposed method can provide estimated position of the object vehicles at every sampling time of ECU. The Mahalanobis distance is used to make correspondence among the measured and predicted objects. Through the experimental results, we validate that the post-processed fusion data give us improved tracking performance. The proposed method obtained two times improvement in the object tracking performance compared to single sensor method (camera or radar sensor) in the view point of roots mean square error.

• 대한임베디드공학회논문지
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• 제10권5호
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• pp.325-333
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• 2015

Vision based night-time vehicle detection has been an emerging research field in various advanced driver assistance systems(ADAS) and automotive vehicle as well as automatic head-lamp control. In this paper, we propose night-time vehicle detection method based on multi-class support vector machine(SVM) that consists of thresholding, labeling, feature extraction, and multi-class SVM. Vehicle light candidate blobs are extracted by local mean based thresholding following by labeling process. Seven geometric and stochastic features are extracted from each candidate through the feature extraction step. Each candidate blob is classified into vehicle light or not by multi-class SVM. Four different multi-class SVM including one-against-all(OAA), one-against-one(OAO), top-down tree structured and bottom-up tree structured SVM classifiers are implemented and evaluated in terms of vehicle detection performances. Through the simulations tested on road video sequences, we prove that top-down tree structured and bottom-up tree structured SVM have relatively better performances than the others.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.13-23
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• 2001

Most current machine vision systems for industrial inspection were developed with one specific task in mind. Hence, these systems are inflexible in the sense that they cannot easily be adapted to other applications. In this paper, a general vision system framework has been developed that can be easily adapted to a variety of industrial web inspection problems. The objective of this system is to automatically locate and identify \\\"defects\\\" on the surface of the material being inspected. This framework is designed to be robust, to be flexible, and to be as computationally simple as possible. To assure robustness this framework employs a combined strategy of top-down and bottom-up control, hierarchical defect models, and uncertain reasoning methods. To make this framework flexible, a modular Blackboard framework is employed. To minimize computational complexity the system incorporates a simple multi-thresholding segmentation scheme, a fuzzy logic focus of attention mechanism for scene analysis operations, and a partitioning if knowledge that allows concurrent parallel processing during recognition.cognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1083-1097
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• 2018

This paper presents a novel range-free localization algorithm based on quantum particle swarm optimization. The proposed algorithm is capable of estimating the distance between two non-neighboring sensors for multi-hop heterogeneous wireless sensor networks where all nodes' communication ranges are different. Firstly, we construct a new cumulative distribution function of expected hop progress for sensor nodes with different transmission capability. Then, the distance between any two nodes can be computed accurately and effectively by deriving the mathematical expectation of cumulative distribution function. Finally, quantum particle swarm optimization algorithm is used to improve the positioning accuracy. Simulation results show that the proposed algorithm is superior in the localization accuracy and efficiency when used in random and uniform placement of nodes for heterogeneous wireless sensor networks.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.768-772
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• 2008

Various scanning systems have been studied in many industrial areas to acquire a range data or to reconstruct an explicit 3D model. Currently optical technology has been used widely by virtue of noncontactness and high-accuracy. In this paper, we describe a 3D laser scanning system developped to reconstruct the 3D surface of a large-scale object such as a curved-plate of ship-hull. Our scanning system comprises of 4ch-parallel laser vision modules using a triangulation technique. For multi laser vision, calibration method based on least square technique is applied. In global scanning, an effective method without solving difficulty of matching problem among the scanning results of each camera is presented. Also minimal image processing algorithm and robot-based calibration technique are applied. A prototype had been implemented for testing.