• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.763-764
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• 2008

Sensing is an important part of a smart home system. Vision sensors are a type of passive systems, which are not sensitive to noise. In this paper, we implement a prototype for stereo vision systems using OpenCV. It is an open source library for computer vision developed by Intel corporation. The prototype will by used for comparing performance among various stereo algorithms and for developing a stereo vision smart camera.

• Journal of Welding and Joining
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• v.16 no.3
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• pp.85-94
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• 1998

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding system, is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. In this paper, developed vision processing techniques are detailed, and their application in welding fabrication is covered. The software for joint tracking system is finally proposed.

• Journal of Mechanical Science and Technology
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• v.20 no.9
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• pp.1418-1427
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• 2006

Windshield wipers play a key role in assuring the driver's safety during precipitation. The traditional wiper systems, however, requires driver's constant attention in adjusting the wiper speed and the intermittent wiper interval because the amount of precipitation on the windshield constantly varies according to time and vehicle's speed. Because the manual adjustment of the wiper distracts driver's attention, which may be a direct cause of traffic accidents, many companies have developed automatic wiper systems using some optical sensors with various levels of success. This paper presents the development of vision-based smart windshield wiper system that can automatically adjust its speed and intermittent interval according to the amount of water drops on the windshield. The system employs various image processing algorithms to detect water drops and fuzzy logic to determine the speed and the interval of the wiper.

• Journal of Sensor Science and Technology
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• v.25 no.4
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• pp.285-290
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• 2016

Human sensing is an important but challenging technology. Unlike other methods for sensing humans, a vision sensor has many advantages, and there has been active research in automatic human detection in camera images. The combination of Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is currently one of the most successful methods in vision-based human detection. However, extracting HOG features from an image is computer intensive, and it is thus hard to employ the HOG method in real-time processing applications. This paper describes an efficient solution to this speed problem of the HOG method. Our method obtains edge information of an image and finds candidate regions where humans very likely exist based on the distribution pattern of the detected edge points. The HOG features are then extracted only from the candidate image regions. Since complex HOG processing is adaptively done by the guidance of the simpler edge detection step, human detection can be performed quickly. Experimental results show that the proposed method is effective in various images.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.791-798
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• 2024

Construction industry records poor safety records annually due to a large number of injuries and accidents on construction jobsite. In order to improve existing safety performance, object detection approaches have been extensively studied using vision-sensing techniques and deep learning algorithms. Unfortunately, an insufficient number of datasets (e.g., images) and challenges that reside in manually collecting quality datasets constitute a significant hurdle in fully deploying object recognition approaches in real construction sites. Although advanced technologies (e.g., virtual reality) have attempted to address such challenges, they have achieved limited success because they still rely on labor-intensive work. A promising alternative is to adopt generative AI-based data augmentation methods attributed to their efficiency in creating realistic visual datasets and proven performance. However, there remain critical knowledge gaps on how such alternatives can be effectively employed by safety managers on real construction sites in terms of practicability and applications. In this context, this study establishes a framework that can identify effective strategies for improving object detection performance (e.g., accuracy) using generative AI technologies. The outcome of this study will contribute to providing guidelines and best practices for practitioners as well as researchers by exploring different generative AI-driven augmentation approaches and comparing the corresponding results in a quantitative manner.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2162-2167
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• 2014

Robots are widely used in various automation processes in industrial applications. Traditionally, it operated under fixed condition by teaching operating positions. Recently, diverse 2D/3D sensors are used together with robot to give more flexibility in operation. In this paper, we deal with automatic manipulation of tie rod in automotive production line. Sensor system consisted of a camera and slit laser is used for the acquisition of 3D information and it is used attached on the robot. Nut runner is used for the manipulation of stop nut and adjust bolt on the tie rod. Detailed procedures for the automatic manipulation of tie rod are presented. In the presented approach, we effectively use 3D information in whole procedure such as computing distance to the tie rod, rotation angle of bolt and nut. Experimental results show the feasibility of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.729-734
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• 2005

One of the important research issues in mobile robot is how to detect the 3D environment fast and accurately, and recognize it. Sensing methods of utilizing laser structured light and/or stereo vision are representatively used among a number of methodologies developed to date. However, the methods are still in need of achieving high accuracy and reliability to be used for real world environments. In this paper to implement a new robotic environmental sensing algorithm is presented by combining the information between intensity image and that of laser structured light image. To see how effectively the algorithm applied to real environments, we developed a sensor system that can be mounted on a mobile robot and tested performance for a series of environments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1863-1866
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• 2005

In this paper we propose a platform that is applicable to low altitude remote sensing. Basic idea of the platform is based on the model helicopter. On big difference from the conventional model helicopter is that our platform has four main rotors. Furthermore, vision control strategy is introduced so that operator can use the platform without any specialized intensive knowledge

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.258-267
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• 1999

An intelligent safety vehicle(ISV) should have an ability to predict the possibility of an accident and help a driver avoid the accident in advance. The basic function of the ISV is to alert the driver by warning when the collision is to occur. For this purpose, the ISV has to function efficiently in sensing the environmental context. While image processing provides lane information, laser radar senses road obstacles including vehicles. By applying a simple clustering algorithm to radar signals, it is possible to obtain the vehicle information. Consequently, we can identify the existence of the vehicle of interest on my lane. The reliability of the sensing algorithm is evaluated by running on the highway with a test vehicle.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.8
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• pp.113-121
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• 1999

It is necessary to calibrate measurement systems to enhance its measurement accuracy. The visual sensing system that is presented in our previous work has to be calibrated, too. It is a multiple mirror system for three-dimensional measurement, which is composed of a camera and a series of mirrors. It is important to calibrate the positions and orientations of the mirrors relative to the camera because they have direct influence on the relationship between the image plane and the task space. This paper presents the calibration method for the visual sensing system. To confirm the measurement performance of the implemented system. its measurement accuracy in measuring the locations in three-dimensional space is investigated. A series of experiments for measuring the locations of the circle-shaped marks are performed. Experimental results show that the sensing system can be effectively used for three-dimensional measurement.