• 한국멀티미디어학회논문지
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• 제19권3호
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• pp.539-547
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• 2016

Automated guided vehicles (AGVs) are widely used in industry. Several types of vision-based AGVs have been studied in order to reduce cost of infrastructure building at floor of workspace and to increase flexibility of changing the navigation path layout. A practical vision-based guideline tracing method is proposed in this paper. A virtual tracing wheel is introduced and adopted in this method, which enables a vision-based AGV to trace a guideline in diverse ways. This method is also useful for preventing damage of the guideline by enforcing the real steering wheel of the AGV not to move on the guideline. Usefulness of the virtual tracing wheel is analyzed through computer simulations. Several navigation tests with a commercial AGV were also performed on a usual guideline layout and we confirmed that the virtual tracing wheel based tracing method could work practically well.

• Computers and Concrete
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• 제33권4호
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• pp.341-348
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• 2024

Ultra-high-performance concrete (UHPC) has received remarkable attentions in civil infrastructure due to its unique mechanical characteristics and durability. UHPC gains increasingly dominant in essential structural elements, while its unique properties pose challenges for traditional inspection methods, as damage may not always manifest visibly on the surface. As such, the need for robust inspection techniques for detecting cracks in UHPC members has become imperative as traditional methods often fall short in providing comprehensive and timely evaluations. In the era of artificial intelligence, computer vision has gained considerable interest as a powerful tool to enhance infrastructure condition assessment with image and video data collected from sensors, cameras, and unmanned aerial vehicles. This paper presents a computer vision-based approach employing deep learning to detect cracks in UHPC beams, with the aim of addressing the inherent limitations of traditional inspection methods. This work leverages computer vision to discern intricate patterns and anomalies. Particularly, a convolutional neural network architecture employing transfer learning is adopted to identify the presence of cracks in the beams. The proposed approach is evaluated with image data collected from full-scale experiments conducted on UHPC beams subjected to flexural and shear loadings. The results of this study indicate the applicability of computer vision and deep learning as intelligent methods to detect major and minor cracks and recognize various damage mechanisms in UHPC members with better efficiency compared to conventional monitoring methods. Findings from this work pave the way for the development of autonomous infrastructure health monitoring and condition assessment, ensuring early detection in response to evolving structural challenges. By leveraging computer vision, this paper contributes to usher in a new era of effectiveness in autonomous crack detection, enhancing the resilience and sustainability of UHPC civil infrastructure.

• 한국컴퓨터정보학회논문지
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• 제24권8호
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• pp.95-103
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• 2019

According to the Statistics Korea in 2017, the 10 leading causes of death contain a cardiac disorder disease, self-injury. In terms of these diseases, urgent assistance is highly required when people do not move for certain period of time. We propose an unusual event detection algorithm to identify abnormal user behaviors using dust, vision and activity sensors in their houses. Vision sensors can detect personalized activity behaviors within the CCTV range in the house in their lives. The pattern algorithm using the dust sensors classifies user movements or dust-generated daily behaviors in indoor areas. The accelerometer sensor in the smartphone is suitable to identify activity behaviors of the mobile users. We evaluated the proposed pattern algorithms and the fusion method in the scenarios.

• 제어로봇시스템학회논문지
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• 제21권12호
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• pp.1178-1184
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• 2015

In conventional robotics, charge-coupled device (CCD) and complementary metal-oxide-semiconductor (CMOS) cameras have been utilized for acquiring vision information. These devices have problems, such as narrow optic angles and inefficiencies in visual information processing. Recently, biomimetic vision sensors for robotic applications have been receiving much attention. These sensors are more efficient than conventional vision sensors in terms of the optic angle, power consumption, dynamic range, and redundancy suppression. This paper presents recent research trends on biomimetic vision sensors and discusses future directions.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1997년도 동계 학술대회 논문집
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• pp.375-384
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• 1997

굴을 까는 작업은 굴의 껍질 에 붙어있는 근육질과 굴 껍질에 붙어있는 hinge를 절단하는 작업을 필요로 한다. 본 논문은 굴을 까는 자동화기계를 개발하기 위한 하나의 단계로서 굴의 hinge 의 위치를 판단하는 computer vision system 의 image processing software (영상처리)개발에 대하여 중점을 두었다. 본 실험에 사용한 굴들은 computer vision system이 굴의 바깥쪽 hinge 표면을 감지할 수 있도록 굴을 물로 씻은 후 굴 껍질의 hinge 부분을 약간 절단하였다. computer vision system은 color video camera를 이용하여 굴의 절단된 hinge표면의 영상을 잡은 후 image processing software를 이용하여 굴의 hinge 위치를 감지하였다. 본 논문에 사용한 computer vision software 는 일반 상용화된 software 와 굴의 hinge 위치를 알아내기 위해 저자가 연구 개발한 software 로 구성하였다. Image 내의 굴의 hinge와 그 밖의 다른 물질을 구별하기 위하여 본 논문의 software 는 4개의 변수 (circularity , Rectangularity, Aspect-ratio , Euclidian Distance)를 이용하였다. 또한 image 내의 굴의 hinge 위치를 쉽고 효과적으로 파악하기 위하여 몇 가지 영상처리, 즉, shrink-expand, thresholding 외의 다른 방법들을 이용하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(3)
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• pp.117-120
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• 2000

This study is to construct a general purpose library for a computer vision system development. The library includes many core algorithms required for computer vision systems such as image Processing algorithms, feature extracting methods, neural networks and etc. We have experimented the efficiency of the library by building a vehicle plate recognition system and the overall time and effort in development could be reduced to a certain extent.

• 반도체디스플레이기술학회지
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• 제10권2호
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• pp.97-102
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• 2011

Lots of 2D vision algorithms have been applied for inspection. However, these 2D vision algorithms have limitation in inspection applications which require 3D information data such as the height of semiconductor chips. Stereo vision is a well known method to measure the distance from the camera to the object to be measured. But it is difficult to apply for inspection directly because of its measurement error. In this paper, we propose two adjustment methods to reduce the error of the measured height data for stereo vision. The weight value based model is used to minimize the mean squared error. The average value based model is used with simple concept to reduce the measured error. The effect of these algorithms has been proved through the experiments which measure the height of semiconductor chips.

• 한국항해학회지
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• 제16권3호
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• pp.77-85
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• 1992

Camera arrangement for depth and image correspondence is very important to the computer vision. Two conventional comera arrangements for stereo computer vision are lateral model and axial motion model. In this paper, using the axial motion stereo camera model, the algorithm for camera focal length measurement and the surface smoothness with the radiance-irradiance is proposed fro 3-dimensional image correspondence on stereo computer vision. By adapting the above algorithm, camera focal length can be measured precisely and the resolution of 3-dimensional image correspondence has been improved comparing to that of the axial motion model without the radiance-irradiance relation.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.119-124
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• 1994

Morden industrial society pursues unmanned system and automation of manufacturing rocess. Abreast with this tendensy, prodution of goods which requires advaned accuracy is increasing as well. According to this, the work sensing time of dressing by monitoring and diagnosis the condition of grinding, which is the representative way in accurate manufacturing, is a important work to prevent serios damages which affect grinding process or products by wearing wheel. Computer vision system is composed, so that grind wheel wurface was acquired by CCD camera and the change of cutting is composed. Then we used autometic threshoding technique from histogram as a way of deviding cutting edge which is used in manufacturing from the other parts. As a result, we are trying to approach unmanned system and sutomation by deciding more accurate time of dressing and by visualizing behavior of grinding wheel by marking use of computer vision.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.111-112
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• 2007

본 논문에서는 멀티프로세서 기반의 고속 영상처리 알고리즘 개발방법에 대해 소개한다. 영상획득 방식의 발전과 더불어 고해상도 영상의 획득이 가능해지고 영상이 컬러화가 되면서 많은 영상처리 응용분야에서 알고리즘 고속화를 필요로 하고 있다. 이러한 수요를 만족시키기 위해서는 최근에 출시되고 있는 멀티프로세서를 최대한 활용할 수 있는 알고리즘 개발이 최우선이다. 본 논문에서는 OpenMP, MIL(Matrox Image Library), OpenCV, IPP(Integrated Performance Primitives), SSE (Streaming SIMD (Single Instruction Multiple Data) Extensions)등 병렬처리와 고속 영상처리 라이브러리를 이용한 알고리즘 개발방법에 대해 소개하고, 각 개발방법에 따른 알고리즘 성능을 분석 및 평가하였다. 실험결과로부터 SSE와 IPP, MIL(Thread)을 이용하여 Mean, Dilation, Erosion, Open, Closing, Sobel등 알고리즘을 구현하여 $4057{\times}4048$크기의 영상에 적용하였을 때 $7{\sim}35msec$의 좋은 성능을 나타내어 기타 방식보다 우수함을 알 수 있었다.