• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.682-688
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• 2000

To improve the performance of a flexible robot arm one of the important things is the vibration displacement measurement of a flexible arm. Many types of sensors have been used to measure it, The most popular has been strain gauges which measures the deflection of the beam,. Photo sensors have also been for detecting beam displacement and accelerometers are often used to measure the beam vibration. But the vibration displacement can be obtained indirectly from these sensors. In this article a vision sensor is used as a displacement sensor to measure the vibration displacement of a flexible robot arm. Several schemes are proposed to reduce the image processing time and increase its accuracy. From the experimental results it is seen that the vision sensor can be an alternative sensor for measuring the vibration displacement and has a potential for on-line tip position control of flexible robot systems.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.179-186
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• 2015

In this paper, a novel lateral control system is proposed for the purpose of improving lane keeping performance which is independent from GPS signals. Lane keeping is a key function for the realization of unmanned driving systems. In order to obtain this objective, a vision sensor based real-time lane detection scheme is developed. Furthermore, we employ a data fusion along with a real-time steering angle of the test vehicle to improve its lane keeping performance. The fused direction data can be obtained by an IMU sensor and vision sensor. The performance of the proposed system was verified by computer simulations along with field tests using MOHAVE, a commercial vehicle from Kia Motors of Korea.

• Smart Structures and Systems
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• v.13 no.6
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• pp.927-942
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• 2014

Structural displacement is an important indicator for assessing structural safety. For structural displacement monitoring, vision-based displacement measurement systems have been widely developed; however, most systems estimate only 1 or 2-DOF translational displacement. To monitor the 6-DOF structural displacement with high accuracy, a vision-based displacement measurement system with a uniquely designed marker is proposed in this paper. The system is composed of a uniquely designed marker and a camera with a zooming capability, and relative translational and rotational displacement between the marker and the camera is estimated by finding a homography transformation. The novel marker is designed to make the system robust to measurement noise based on a sensitivity analysis of the conventional marker and it has been verified through Monte Carlo simulation results. The performance of the displacement estimation has been verified through two kinds of experimental tests; using a shaking table and a motorized stage. The results show that the system estimates the structural 6-DOF displacement, especially the translational displacement in Z-axis, with high accuracy in real time and is robust to measurement noise.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.83-83
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• 2000

Recently, Vision system has being used all around industry. Sensor systems are used for Mark Reader, for example, optical scanning is proximity sensor system, have many disadvantages, such as, lacking user interface and difficulty to store original specimens. In contrast with this, Vision systems for Mark Reader has many advantages, including function conversion to achieve other work, high accuracy, high speed, etc. In this thesis, we have researched the development of Mark Reader by using a Vision system. The processing course of this s)'stem is consist to Image Pre-Processing such as noise reduction, edge detection, threshold processing. And then, we have carried out camera calibration to calibrate images which are acquired from camera. After searching for reference point within scanning area(60pixe1${\times}$30pixe1), we have calculated points crossing by using line equations. And then, we decide to each ROI(region of interest) which are expressed by four points. Next we have converted absolute coordinate into relative coordinate for analysis a translation component. Finally we carry out Mark Reading with images classified by six patterns. As a result of experiment which follows the algorithm has proposed, we have get error within 0.5% from total image.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1030-1035
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• 2014

Machine vision inspection systems have replaced human inspectors in defect inspection fields for several decades. However, the inspection results of machine vision are often affected by small changes of illumination. When small changes of illumination appear in image histograms, the influence of illumination can be decreased by transformation of the histogram. In this paper, we propose an enhanced histogram matching algorithm which corrects distorted histograms by variations of illumination. We use the resolution resizing method for an optimal matching of input and reference histograms and reduction of quantization errors from the digitizing process. The proposed algorithm aims not only for improvement of the accuracy of defect detection, but also robustness against variations of illumination in machine vision inspection. The experimental results show that the proposed method maintains uniform inspection error rates under dramatic illumination changes whereas the conventional inspection method reveals inconsistent inspection results in the same illumination conditions.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.285-288
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• 2005

We propose a novel programmable miniature vision module based on a custom designed analog VLSI (aVLSI) chip. The vision module consists of the optical flow vision sensor embedded with commercial off-the-shelves digital hardware; in our case is the Intel XScale PXA270 processor enforced with a programmable gate array device. The aVLSI sensor provides gray-scale imager data as well as smooth optical flow estimates, thus each pixel gives a triplet of information that can be continuously read out as three independent images. The particular computational architecture of the custom designed sensor, which is fully parallel and also analog, allows for efficient real-time estimations of the smooth optical flow. The Intel XScale PXA270 controls the sensor read-out and furthermore allows, together with the programmable gate array, for additional higher level processing of the intensity image and optical flow data. It also provides the necessary standard interface such that the module can be easily programmed and integrated into different vision systems, or even form a complete stand-alone vision system itself. The low power consumption, small size and flexible interface of the proposed vision module suggests that it could be particularly well suited as a vision system in an autonomous robotics platform and especially well suited for educational projects in the robotic sciences.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.41-52
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• 2014

In this paper, O-ring size measurement algorithm based on a small machine vision inspection equipment which can replace a expensive and large machine vision inspection equipment is presented. The small machine vision inspection equipment acquires a image from a CCD camera shooting a measurement plane which located on a back light and the proposed size measurement algorithm is apply to the image. For improvement of size measurement accuracy, camera lens distortion correction and perspective distortion correction are conducted by software technique. Consider O-ring's shape, ellipse fitting model is applied. In order to increase the reliability of ellipse fitting, RANSAC algorithm is applied.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.521-524
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• 2004

Recently, acgis of authentication and crcator's copyright has become a matter of great concern by the diffusion of multimedia technique and the growth of the internet and the easily duplicated property of digital data. Consequently, many active researches have been made to protect copyright and to assure integrity by inserting watermark into the digital data. In this paper, watermark is repealed through the entire image and adapted to the content of the image. Achieved by an underlying process of transforming the digital image to the frequency domain by wavelet transform, which has three (vertical, horizontal, diagonal) directions and Multi-resolution features, and then choosing frequency area inferior to the human perceptibility and significant for invisible and robust watermark. We realize wavelet based image watermarking using Machine Vision of LabVIEW.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.2
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• pp.223-229
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• 2017

Recently, robotic bin-picking tasks have drawn considerable attention, because flexibility is required in robotic assembly tasks. Generally, stereo camera systems have been used widely for robotic bin-picking, but these have two limitations: First, computational burden for solving correspondence problem on stereo images increases calculation time. Second, errors in image processing and camera calibration reduce accuracy. Moreover, the errors in robot kinematic parameters directly affect robot gripping. In this paper, we propose a method of correcting the bin-picking error by using trinocular vision system which consists of two stereo cameras andone hand-eye camera. First, the two stereo cameras, with wide viewing angle, measure object's pose roughly. Then, the 3rd hand-eye camera approaches the object, and corrects the previous measurement of the stereo camera system. Experimental results show usefulness of the proposed method.

• Smart Structures and Systems
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• v.20 no.5
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• pp.563-572
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• 2017

The safety of structures is closely associated with the structural out-of-plane behavior. In particular, long and slender beam structures have been increasingly used in the design and construction. Therefore, an evaluation of the lateral and torsional behavior of a structure is important for the safety of the structure during construction as well as under service conditions. The current contact measurement method using displacement meters cannot measure independent movements directly and also requires caution when installing the displacement meters. Therefore, in this study, a vision-based system was used to measure the in-plane and out-of-plane displacements of a structure. The image processing algorithm was based on reference objects, including multiple targets in Lab color space. The captured targets were synchronized using a load indicator connected wirelessly to a data logger system in the server. A laboratory beam test was carried out to compare the displacements and rotation obtained from the proposed vision-based measurement system with those from the current measurement method using string potentiometers. The test results showed that the proposed vision-based measurement system could be applied successfully and easily to evaluating both the in-plane and out-of-plane movements of a beam including twisting rotation.