• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.715-720
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• 2005

This paper presents a hybrid recognition method of first moment of face image and principal component analysis(PCA). First moment is applied to reduce the dimension by shifting to the centroid of image, which is to exclude the needless backgrounds in the face recognitions. PCA is implemented by single layer neural network which has a teaming rule of Foldiak algorithm. It has been used as an alternative method for numerical PCA. PCA is to derive an orthonormal basis which directly leads to dimensionality reduction and possibly to feature extraction of face image. The proposed method has been applied to the problems for recognizing the 48 face images(12 Persons $\ast$ 4 scenes) of 64$\ast$64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate). The negative angle has been relatively achieved more an accurate similarity than city-block or Euclidean.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.178-181
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• 2011

With the development of mobile devices and intelligent surveillance system loaded with pan/tilt cameras, object tracking with non-stationary cameras has become a topic with increasing importancy. Since it is difficult to model a background image in a non-stationary camera environment, colors and texture are the most important features in the tracking algorithm. However, colors in the background similar to those in the target arise instability in the tracking. Recently, we proposed a robust color based tracking algorithm that uses an area weighted centroid shift. In this letter, we update the model such that it becomes more stable against background colors. The proposed algorithm also incorporates time filtering by adding an additional energy term to the energy functional.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.05a
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• pp.450-453
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• 2008

During the drawing of reentrant section like a spline, the unfilled in the corner of dies or the bended product emerges from the large reduction of area, the complex shaped sections and other nonuniform properties in material and lubrication conditions. In this study, the drawing of the spline section with the non-rotary symmetry from a circular aluminum billet has been analyzed by using commercial code DEFORM-3D. A new die construction method preventing the spline from the drawback of bending and the unfilled defect has been suggested and verified through the analysis using centroid shift method and the hybrid construction between converged and diverged profile.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.2
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• pp.167-173
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• 2017

In this paper, the characterization of the vertical position of trapped charges in the charge-trap flash (CTF) memory is performed in the novel CTF memory cell with gate-all-around structure using technology computer-aided design (TCAD) simulation. In the CTF memories, injected charges are not stored in the conductive poly-crystalline silicon layer in the trapping layer such as silicon nitride. Thus, a reliable technique for exactly locating the trapped charges is required for making up an accurate macro-models for CTF memory cells. When a programming operation is performed initially, the injected charges are trapped near the interface between tunneling oxide and trapping nitride layers. However, as the program voltage gets higher and a larger threshold voltage shift is resulted, additional charges are trapped near the blocking oxide interface. Intrinsic properties of nitride including trap density and effective capture cross-sectional area substantially affect the position of charge centroid. By exactly locating the charge centroid from the charge distribution in programmed cells under various operation conditions, the relation between charge centroid and program operation condition is closely investigated.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.7-14
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• 2006

This paper presents an efficient face recognition method using both first moment of image and basis images. First moment which is a method for finding centroid of image, is applied to exclude the needless backgrounds in the face recognitions by shifting to the centroid of face image. Basis images which are the face features, are respectively extracted by principal component analysis(PCA) and fixed-point independent component analysis(FP-ICA). This is to improve the recognition performance by excluding the redundancy considering to second- and higher-order statistics of face image. The proposed methods has been applied to the problem for recognizing the 48 face images(12 persons*4 scenes) of 64*64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed methods has a superior recognition performances(speed, rate) than conventional PCA and FP-ICA without preprocessing, the proposed FP-ICA has also better performance than the proposed PCA. The city-block has been relatively achieved more an accurate similarity than Euclidean or negative angle.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.33-40
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• 2006

This paper presents an efficient face recognition method using both first moment of image and eigenvector. First moment is a method for finding centroid of image, which is applied to exclude the needless backgrounds in the face recognitions by shitting to the centroid of face image. Eigenvector which are the basis images as face features, is extracted by principal component analysis(PCA). This is to improve the recognition performance by excluding the redundancy considering to second-order statistics of face image. The proposed methods has been applied to the problem for recognizing the 60 face images(15 persons *4 scenes) of 320*243 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. In case of the 45 face images, the experimental results show that the recognition rate of the proposed methods is about 1.6 times and its the classification is about 5.6 times higher than conventional PCA without preprocessing. The city-block has been relatively achieved more an accurate classification than Euclidean or negative angle.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.629-632
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• 2007

While conventional interferometric SAR (InSAR) technique is an excellent tool for displacement observation, it is only sensitive to one-dimensional deformation along the satellite's line-of-sight (LOS). Recently, a multiple aperture interferogram (MAI) technique has been developed to overcome this drawback. This method successfully extracted along-track displacements from InSAR data, based on split-beam InSAR processing, to create forward- and backward- looking interferograms, and was superior to along-track displacements derived by pixel-offset algorithm. This method is useful to measure along-track displacements. However, it does not only decrease the coherence of MAI because three co-registration and resampling procedures are required for producing MAI, but also is confined to a suitable interferometric pair of SAR images having zero Doppler centroid. In this paper, we propose an efficient and robust method to generate MAI from interferometric pair having non-zero Doppler centroid. The proposed method efficiently improves the coherence of MAI, because the co-registration of forward- and backward- single look complex (SLC) images is carried out by time shift property of Fourier transform without resampling procedure. It also successfully removes azimuth flat earth and topographic phases caused by the effect of non-zero Doppler centroid. We tested the proposed method using ERS images of the Mw 7.1 1999 California, Hector Mine Earthquake. The result shows that the proposed method improved the coherence of MAI and generalized MAI processing algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.581-587
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• 2005

This paper presents a hybrid face recognition method of both the first moment of image and the independent component analysis(ICA) of fixed point(FP) algorithm based on Newton method. First moment is a method for finding centroid of image, which is applied to exclude the needless backgrounds in the face recognitions by shifting to the centroid of face image. FP-ICA is also applied to find a set of independent basis images for the faces, which is a set of statistically independent facial features. The proposed method has been applied to the problem for recognizing the 48 face images(12 persons o 4 scenes) of 64*64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate) than conventional FP-ICA without preprocessing. The city-block has been relatively achieved more an accurate similarity than Euclidean or negative angle.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.236-247
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• 2010

Recently, mean shift tracking algorithms have been proposed which use the information of color histogram together with some spatial information provided by the kernel. In spite of their fast speed, the algorithms are suffer from an inherent instability problem which is due to the use of an isotropic kernel for spatiality and the use of the Bhattacharyya coefficient as a similarity function. In this paper, we analyze how the kernel and the Bhattacharyya coefficient can arouse the instability problem. Based on the analysis, we propose a novel tracking scheme that uses a new representation of the location of the target which is constrained by the color, the area, and the spatiality information of the target in a more stable way than the mean shift algorithm. With this representation, the target localization in the next frame can be achieved by one step computation, which makes the tracking stable, even in difficult situations such as low-rate-frame environment, and partial occlusion.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.41.1-41.1
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• 2016

The Galactic center, Sagittarius A* (Sgr A*), is the closest supermassive black hole and emits synchrotron radiation. It provides great opportunity to study the origin of mm/sub-mm emission. Currently, two competing models have been suggested as a jet base and a radiatively inecient accretion flow (RIAF). To unveil the properties, the extremely high resolution(${\sim}10{\mu}as$) corresponding to the projected Schwarzschild radius of ~0.1AU is necessary. With KVN, a jet model can be tested by multi- frequency simultaneous observations because the optically thick surface in a jet (i.e. radio core) moves toward the center at a higher frequency. We conducted 8 observations with KVN at 43/86GHz in 2015, and found that the measured positional shift to the reference calibrator, J1744-3116, was ~0.3 mas to the south of Sgr A* using the source frequency phase referencing (SFPR) at Q/W bands for the first time. With the result, in the future, we will attempt to measure the variation of source position shifts that can constrain the direction of approaching jets and the variability of black hole activity of Sgr A*.