• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.467-473
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• 2007

In this paper, we present a position-based robot hand tracking scheme where a pan-tilt camera is controlled such that a robot hand is always shown in the center of an image frame. We calculate the rotation angles of a pan-tilt camera by transforming the coordinate systems. In order to identify the model parameters, we applied two optimization techniques: a nonlinear least square optimizer and a particle swarm optimizer. From the simulation results, it is shown that the considered parameter identification problem is characterized by a highly multimodal landscape; thus, a global optimization technique such as a particle swarm optimization could be a promising tool to identify the model parameters of a robot hand tracking system, whereas the nonlinear least square optimizer often failed to find an optimal solution even when the initial candidate solutions were selected close to the true optimum.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.7
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• pp.313-318
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• 2006

An automatic sample centering system is underway at the protein crystallography beam line of the Pohang Light Source to improve the efficiency of the crystal screening process. A sample pin which contains a protein crystal is mounted on a goniometer head. Then the crystal should be moved to the center of X-ray beam by controlling the motorized goniometer to obtain diffraction data. Since the X-ray beam is located at the center of the image obtained from the CCD camera when the image of the sample pin is in focus, an auto-focusing algorithm is a very important part in the auto-sample-centering system. However the results of applying several well-known auto focusing algorithms directly to the images are not satisfactory owing to the following factors: misalignment of CCD camera, non-uniform cryo-stream in the background of the image and the supporter of the loop. The performance of an auto-focusing algorithm can be increased if the algorithm is applied to only the loop region identified. Non-uniform cryo-stream and a various illumination condition and a stain, which is shown in the image, are main obstacles to loop region identification. In this paper, a simple loop region identification algorithm, which can solve these problems, is proposed and the effective ness of the proposed scheme is shown by applying the auto-focusing algorithm to the loop region identified.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.61-68
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• 2008

A set of modal parameters of a stay-cable have been extracted from a moving picture captured by a digital camera supported by shaking hands. It is hard to identify the center of targets attached on the cable surface from the blurred cable motion image, because of the high speed motion of cable, low sampling frequency of camera, and the shaking effect of camera. This study proposes a multi-template matching algorithm to resolve such difficulties. In addition, a sensitivity-based system identification algorithm is introduced to extract the natural frequencies and damping ratios from the ambient cable vibration data. Three sets of vibration tests are conducted to examine the validity of the proposed algorithms. The results show that the proposed technique is pretty feasible for extracting modal parameters from the severely shaking motion pictures.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.1
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• pp.76-84
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• 2012

This paper presents the measurement system of arrow's point of impact using laser scan camera and describes the image calibration method. The calibration process of distorted image is primarily divided into explicit and implicit method. Explicit method focuses on direct optical property using physical camera and its parameter adjustment functionality, while implicit method relies on a calibration plate which assumed relations between image pixels and target positions. To find the relations of image and target position in implicit method, we proposed the performance criteria based polynomial theorem model that overcome some limitations of conventional image calibration model such as over-fitting problem. The proposed method can be verified with 2D position of arrow that were taken by SICK Ranger-D50 laser scan camera.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.12
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• pp.1229-1236
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• 2008

A set of modal parameters of a stay-cable have been extracted fi:on a moving picture captured by a digital camera supported by shaking hands. It is hard to identify the center of targets attached on the cable surface from the blurred cable motion image, because of the high speed motion of cable, low sampling frequency of camera, and the shaking effect of camera. This study proposes a multi-template matching algorithm to resolve such difficulties. In addition, a sensitivity-based system identification algorithm is introduced to extract the natural frequencies and damping ratios from the ambient cable vibration data. Three sets of vibration tests are conducted to examine the validity of the proposed algorithms. The results show that the proposed technique is pretty feasible for extracting modal parameters from the severely shaking motion pictures.

• KSCI Review
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• v.26 no.2
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• pp.1-7
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• 2018

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.915-916
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• 2008

We propose a clustering based object feature matching for identification of same object in multi-camera system. The method is focused on ease to system initialization and extension. Clustering is used to estimate parameters of Gaussian mixture models of objects. A similarity measure between models are determined by Kullback-Leibler divergence. This method can be applied to occlusion problem in tracking.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1046-1050
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• 2003

In general, conventional user identification systems require users to carry a TAG or badge or to remember ID and password. Though biometric identification systems may relieve these problems, they are susceptible to environmental noise to some degree. We propose a natural user identification system, ubiFloor, exploiting user's walking pattern to identify the user. The system identifies a user, while tracking the user's location, with a set of simple ON/OFF switch sensors or equipments. Experimental results show that the proposed system can recognize the registered users at the rate of 92%. Future improvement in recognition rate may be achieved by combining other sensors such as camera, microphone, etc.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• Applied Biological Chemistry
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• v.41 no.2
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• pp.160-165
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• 1998

Current discriminating technique of rice variety is known to be not objective till this time because of depending on naked eye of well trained inspector. DNA finger print method based on genetic character of rice has been indicated inappropriate for on-site application, because the method need much labor and skilled expert. The purpose of this study was to develops the identification technique of polished rice varieties using CCD camera images. To minimize the noise of the captured image, thresholding and median filtering were carried out, and edge was extracted from the image data. Image data after pretreatment of normalize and FFT(fast fourier transform) were used for library model and feedforward backpropagation neural network model. Image processing technique using CCD camera could discriminate the variety of rice with high accuracy in case of quite different rice of shape, but the accuracy was reached at 85% in the similar shape of rice.