• Journal of Korea Multimedia Society
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• v.21 no.1
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• pp.51-60
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• 2018

We present a real-time interactive particle-art with human motion based on computer vision techniques. We used computer vision techniques to reduce the number of equipments that required for media art appreciations. We analyze pros and cons of various computer vision methods that can adapted to interactive digital media art. In our system, background subtraction is applied to search an audience. The audience image is changed into particles with grid cells. Optical flow is used to detect the motion of the audience and create particle effects. Also we define a virtual button for interaction. This paper introduces a series of computer vision modules to build the interactive digital media art contents which can be easily configurated with a camera sensor.

• International Journal of Korean Welding Society
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• v.2 no.2
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• pp.57-60
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• 2002

Generally, the laser vision sensor makes it possible design a highly reliable and precise range sensor at a low cost. When the laser vision sensor is applied to lap joint welding, however. there are many limitations. Therefore, a specially-designed hardware system has to be used. However, if the multi-lines are used instead of a single line, multi-range data .:an be generated from one image. Even under a set condition of 30fps, the generated 2D range data increases depending on the number of lines used. In this study, a laser vision sensor with a multi-line pattern is developed with conventional CCD camera to carry out high speed seam tracking in lap joint welding.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.409-415
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• 2022

In computer vision, an image of a measurement target is acquired using a camera. And feature values, vectors, and regions are detected by applying algorithms and library functions. The detected data is calculated and analyzed in various forms depending on the purpose of use. Computer vision is being used in various places, especially in the field of automatically recognizing automobile parts or measuring the quality. Computer vision is being used as the term machine vision in the industrial field, and it is connected with artificial intelligence to judge product quality or predict results. In this study, a vision system for judging the quality of automobile parts was built, and the results were compared by applying five machine learning classification models to the produced data.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.34-41
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• 1997

The dimension measurement problem of products has been a major concern in the quality control in the industrial fields. A non-contacting measurement system using the vision sensor is proposed in this paper. The system consists of a CCD camera for the image capture, a frame grabber for the acquired image processing, a laser unit for the illumination, scanning unit for the measurement, and a personal computer for the geometry computation. The slit beam which is generated by passing the laser beam through a cylin- drical lens is fired to the axial-symmetric object on the rotating plate. The image of objects reflected by the laser slit beam, acquired by the CCD camera, becomes much brighter than the other parts of objects. After the histogram of brightness for the captured image is calculated, low intensity pixels are filtered out by threshold method. The performance of proposed measurement system is obtained for several different axial symmetric objects. The proposed system is verified as a good tool for measuring axial-symmetric parts in a limited condition with a minor investment cost.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.11a
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• pp.207-217
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• 2000

In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are angle, distance error and real position of other vehicles, we should calculate the reference steering angle.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.7
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• pp.557-566
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• 2018

In this paper, a vision-based relative navigation system is addressed for autonomous aerial refueling. In the air-to-air refueling, it is assumed that the tanker has the drogue, and the receiver has the probe. To obtain the relative information from the drogue, a vision-based imaging technology by infra-red camera is applied. In this process, the relative information is obtained by using Gaussian Least Squares Differential Correction (GLSDC), and Levenberg-Marquadt(LM), where the drouge geometric information calculated through image processing is used. These two approaches proposed in this paper are analyzed through numerical simulations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.4
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• pp.289-295
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• 2015

This paper describes a ground monocular vision-based measurement algorithm measuring relative range and position of aircraft using the information of wingspan and optical parameters for the camera. A technique obtaining an aircraft image is also described in this paper. This technique can be used as external measurement for autonomous landing instead of ILS. To verify the performance of these algorithms, flight experiment is performed using light sport aircraft with GPS and monocular camera. Finally we obtained the reasonable RMSE of 1.85m is obtained.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.547-554
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• 2013

This paper proposes a novel formation algorithm of identical robots based on object tracking method using omni-directional images obtained through fisheye lenses which are mounted on the robots. Conventional formation methods of multi-robots often use stereo vision system or vision system with reflector instead of general purpose camera which has small angle of view to enlarge view angle of camera. In addition, to make up the lack of image information on the environment, robots share the information on their positions through communication. The proposed system estimates the region of robots using SURF in fisheye images that have $360^{\circ}$ of image information without merging images. The whole system controls formation of robots based on moving directions and velocities of robots which can be obtained by applying Lucas-Kanade Optical Flow Estimation for the estimated region of robots. We confirmed the reliability of the proposed formation control strategy for multi-robots through both simulation and experiment.

• Proceedings of the Korean Society of Laser Processing Conference
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• 2005.11a
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• pp.50-56
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• 2005

The robot systems are widely used in the many industrial field as well as welding manufacturing. The essential tasks to operate the welding robot are the acquisition of the position and/or shape of the parent metal. For the seam tracking or the robot tracking, many kinds of contact and non-contact sensors are used. Recently, the vision is most popular. In this paper, the development of the system which measures the shape of the welding part is described. This system uses the line-type structured laser diode and the vision sensor. It includes the correction of radial distortion which is often found in the image taken by the camera with short focal length. The Direct Linear Transformation (DLT) method is used for the camera calibration. The three dimensional shape of the parent metal is obtained after simple linear transformation. Some demos are shown to describe the performance of the developed system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.19-26
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• 2004

In this paper, we suggest a 3D vision inspection method which use only one camera. If we have the database of pattern and can recognize the object, and also estimate the rotated shape of the parts, we can inspect the parts using only one image. We used the 3D database and the 2D geometrical pattern matching, and the rotation transition theory about the algorithm. As the results, we could have the capability of the recognition and inspection of the rotated object through the estimation of rotation an81e. We applied our suggested algorithm to the inspection of typical IC and capacitor, and compared our suggested algorithm with the conventional 2D inspection method and the feature space trajectory method.