• Korean Journal of Materials Research
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• v.31 no.6
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• pp.331-338
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• 2021

Ti-Al-Si target and Cr-Si target are sputtered alternately to develop a multi-layered nitride coating on a steel mold to improve die-casting lifetime. Prior to the multi-layer deposition, a CrN layer is developed as a buffer layer on the mold to suppress the diffusion of reactive elements and enhance the cohesive strength of the multi-layer deposition. Approximately 50 nm CrSiN and TiAlSiN layers are deposited layer by layer, and form about three ㎛-thickness of multi-layered coating. From the observation of the uncoated and coated steel molds after the acceleration experiment of liquid metal injection casting, the uncoated mold is severely eroded by the adhesion of molten metallic glass. On the other hand, the multi-layer coating on the mold prevents element diffusion from the metallic glass and mold erosion during the experiment. The multi-layer structure of the coating transforms the nano-composite structured coating during the acceleration test. Since the nano-composite structure disrupts element diffusion to molten metallic glass, despite microstructure changes, the coating is not eroded by the 1,050 ℃ molten metallic glass.

• The Journal of Korea Robotics Society
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• v.12 no.1
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• pp.33-41
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• 2017

We present a region-based approach for accurate pose estimation of small mechanical components. Our algorithm consists of two key phases: Multi-view object co-segmentation and pose estimation. In the first phase, we explain an automatic method to extract binary masks of a target object captured from multiple viewpoints. For initialization, we assume the target object is bounded by the convex volume of interest defined by a few user inputs. The co-segmented target object shares the same geometric representation in space, and has distinctive color models from those of the backgrounds. In the second phase, we retrieve a 3D model instance with correct upright orientation, and estimate a relative pose of the object observed from images. Our energy function, combining region and boundary terms for the proposed measures, maximizes the overlapping regions and boundaries between the multi-view co-segmentations and projected masks of the reference model. Based on high-quality co-segmentations consistent across all different viewpoints, our final results are accurate model indices and pose parameters of the extracted object. We demonstrate the effectiveness of the proposed method using various examples.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.115-115
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• 2008

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.6
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• pp.146-151
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• 2016

In this paper, we present a method for estimating the ratio of CPA distance to velocity of underwater target using target bearing information in CPA situation. This ratio can be estimated by previous research which is Envelope CPA using proximity sensor but it has low performance if the target is close to receiver sensor or bigger interference caused by multi-path effects. Therefore we propose a Bearing CPA technique using a target bearing information as a way to overcome.

• Journal of Korea Multimedia Society
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• v.15 no.2
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• pp.195-203
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• 2012

This paper proposes ground target classification algorithm based on decision fusion and feature extraction method using multi-sensor images. The decisions obtained from the individual classifiers are fused by applying a weighted voting method to improve target recognition rate. For classifying the targets belong to the individual sensors images, features robust to scale and rotation are extracted using the difference of brightness of CM images obtained from CCD image and the boundary similarity and the width ratio between the vehicle body and turret of target in FLIR image. Finally, we verity the performance of proposed ground target classification algorithm and feature extraction method by the experimentation.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.21-28
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• 2016

In this paper, we propose a fast small target detection method using multiple filters, and describe system implementation using IPP libraries. To detect small targets in Infra-Red images, it is mandatory that you should apply a filter to eliminate a background and identify the target information. Moreover, by using a suitable algorithm for the environments and characteristics of the target, the filter must remove the background information while maintaining the target information as possible. For this reason, in the proposed method we have detected small targets by applying multi area(spatial) filters in a low luminous environment. In order to apply the multi spatial filters, the computation time can be increased exponentially in case of the sequential operation. To build this algorithm in real-time systems, we have applied IPP library to secure a software optimization and reduce the computation time. As a result of applying real environments, we have confirmed a detection rate more than 90%, also the computation time of the proposed algorithm have been improved about 90% than a typical sequential computation time.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.129-135
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• 2011

In this paper, we propose a multi target's elevation angle estimation method using multi beam forming technique. This method make a stacked beam to digital processing a received signal in array element. There can be desired receiving beam to application weight value at antenna element in beam forming. Currently, we are to make multi stacked beam using fast fourier transform in stead of phase shifter to be a computer performance much improvement. Also, we improve multi beam directivity using beam steering error correction technique in order to beam steering to desired direction in receiver. Through simulation, we show that the proposed elevation estimation method based on fast fourier transform and beam steering error correction technique, improves th performance of target estimation compared to previous method.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1259-1262
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• 1998

This paper introduced a scheme for finding the relationships between the measurements and tracks in multi-target tracking (MTT). We considered the relationships between targets and measurements as MRF and assumed a priori as a Gibbs distribution. An energy function is defined over the measurement space, as accurately as possible so that it may incorporate most of the important natural constraints. To find the minimizer of the energy function, we derived a new equation of closed form.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.04a
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• pp.24-30
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• 1990

An improved algorithm for simulation of multi-variate random processes has been presented. It is based on the spectral representation method. The conventional methods give sample time histories which satisfy the target spectral density matrix only in the sense of ensemble average. However, the present method can generate sample functions which satisfy the target spectra in the ergodic sense. Example analysis is given for the simulation of earthquake accelerations with three components.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.5-8
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• 2000

This paper introduced a scheme for finding an optimal association matrix that represents the relationships between the measurements and tracks in multi-target tracking of Radar system. We considered the relationships between targets and measurements as MRF and assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space, that may incorporate most of the important natural constraints.