• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.200-208
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• 2003

This paper proposes a separation and feature extraction of image signals using the independent component analysis(ICA) based on neural networks of efficient learning rule. The proposed learning rule is a hybrid fixed-point(FP) algorithm based on secant method and momentum. Secant method is applied to improve the performance by simplifying the 1st-order derivative computation for optimizing the objective function, which is to minimize the mutual informations of the independent components. The momentum is applied for high-speed convergence by restraining the oscillation in the process of converging to the optimal solution. The proposed algorithm has been applied to the composite images generated by random mixing matrix from the 10 images of $512\times512$-pixel. The simulation results show that the proposed algorithm has better performances of the separation speed and rate than those using the FP algorithm based on Newton and secant method. The proposed algorithm has been also applied to extract the features using a 3 set of 10,000 image patches from the 10 fingerprints of $256\times256$-pixel and the front and the rear paper money of $480\times225$-pixel, respectively, The simulation results show that the proposed algorithm has also better extraction speed than those using the another methods. Especially, the 160 basis vectors(features) of $16\times16$-pixel show the local features which have the characteristics of spatial frequency and oriented edges in the images.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.281-288
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• 2004

In order to extract and analyze complex features of the behavior of animals in response to external stimuli such as toxic chemicals, we implemented an adaptive computational method to characterize changes in the behavior of chironomids in response to treatment with the insecticide, diazinon. In this paper, we propose an energy minimization model to extract the features of response behavior of chironomids under toxic treatment, which is applied on the image of velocity vectors. It is based on the improved active contour model and the variations of the energy functional, which are produced by the evolving active contour. The movement tracks of individual chironomid larvae were continuously measured in 0.25 second intervals during the survey period of 4 days before and after the treatment. Velocity on each sample track at 0.25 second intervals was collected in 15-20 minute periods and was subsequently checked to effectively reveal behavioral states of the specimens tested. Active contour was formed around each collection of velocities to gradually evolve to find the optimal boundaries of velocity collections through processes of energy minimization. The active contour which is improved by T. Chan and L. Vese is used in this paper. The energy minimization model effectively revealed characteristic patterns of behavior for the treatment versus no treatment, and identified changes in behavioral states .is the time progressed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2109-2119
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• 2001

In this paper, a fast information extraction algorithm for object-based MPEG-4 application from MPEG-2 bit-steam is proposed. For object-based MPEG-4 conversion, we need to extract such information as object-image, shape-image, macro-block motion vector, and header information from MPEG-2 bit-stream. If we use the extracted information, fast conversion for object-based MPEG-4 is possible. The proposed object extraction algorithm has two important steps, namely the motion vectors extraction from MPEG-2 bit-stream and the watershed algorithm. The algorithm extracts objects using user\`s assistance in the intra frame and tracks then in the following inter frames. If we have an unsatisfactory result for a fast moving object, the user can intervene to correct the segmentation. The proposed algorithm consist of two steps, which are intra frame object extracts processing and inter frame tracking processing. Object extracting process is the step in which user extracts a semantic object directly by using the block classification and watersheds. Object tacking process is the step of the following the object in the subsequent frames. It is based on the boundary fitting method using motion vector, object-mask, and modified watersheds. Experimental results show that the proposed method can achieve a fast conversion from the MPEG-2 bit-stream to the object-based MPEG-4 input.

• Journal of the Korea Computer Graphics Society
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• v.18 no.4
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• pp.1-8
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• 2012

We present improved deformation energy to enhance the visual quality of a shape deformation technique, where we preserve the local structure of an input planar shape. The deformation energy, in general, consists of several constraints such as Laplacian coordinate constraint to preserve the quality of deformed silhouette edges, mean value coordinates and edge length constraints to preserve the quality of deformed internal shape, and user-specified position constraints to control the shape deformation. When the positions of user-specified vertices change, shape deformation techniques compute the positions of the other vertices by means of nonlinear least squares optimization to minimize the deformation energy. When a user-specified vertex changes its position rapidly, it is frequently observed that the visual quality of the deformed shape decrease rapidly, which is mainly caused by unnecessary enlargement of the Laplacian vectors and unnecessary change of the edge directions along the boundary of the shape. In this paper, we propose improved deformation energy by prohibiting the Laplacian and edge length constraints from changing unnecessarily. The proposed deformation energy incorporated with well-known optimization technique can enhance the visual quality of shape deformation along the silhouette and within the interior of the planar shape while sacrificing only a little execution time.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.11
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• pp.101-109
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• 2009

Generally, depth cache and pixel cache of 3D graphics are designed by using write-back scheme for efficient use of memory bandwidth. Also, there are write after read operations of same address or only write operations are occurred frequently in 3D graphics cache. If a cache miss is detected, an access to the external memory for write back operation and another access to the memory for handling the cache miss are operated simultaneously. So on frequent cache miss situations, as the memory access bandwidth limited, the access time of the external memory will be increased due to memory bottleneck problem. As a result, the total performance of the processor or the IP will be decreased, also the problem will increase peak power consumption. So in this paper, we proposed a novel early write back cache architecture so as to solve the problems issued above. The proposed architecture controls the point when to access the external memory as to copy the valid data block. And this architecture can improve the cache performance with same hit ratio and same capacity cache. As a result, the proposed architecture can solve the memory bottleneck problem by preventing intensive memory accesses. We have evaluated the new proposed architecture on 3D graphics z cache and pixel cache on a SoC environment where ARM11, 3D graphic accelerator and various IPs are embedded. The simulation results indicated that there were maximum 75% of performance increase when using various simulation vectors.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.6
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• pp.49-59
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• 2008

SIFT(Scale Invariant Feature Transform) is an algorithm to extract vectors at pixels around keypoints, in which the pixel colors are very different from neighbors, such as vortices and edges of an object. The SIFT algorithm is being actively researched for various image processing applications including 3-D image constructions, and its most computation-intensive stage is a keypoint localization. In this paper, we develope a fixed-point model of the keypoint localization and propose its efficient hardware architecture for embedded applications. The bit-length of key variables are determined based on two performance measures: localization accuracy and error rate. Comparing with the original algorithm (implemented in Matlab), the accuracy and error rate of the proposed fixed point model are 93.57% and 2.72% respectively. In addition, we found that most of missing keypoints appeared at the edges of an object which are not very important in the case of keypoints matching. We estimate that the hardware implementation will give processing speed of $10{\sim}15\;frame/sec$, while its fixed point implementation on Pentium Core2Duo (2.13 GHz) and ARM9 (400 MHz) takes 10 seconds and one hour each to process a frame.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.2 s.332
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• pp.73-82
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• 2005

Test data volume and power consumption for scan vectors are two major problems in system-on-a-chip testing. Therefore, this paper proposes a new test data compression/decompression method for low power testing. The method is based on analyzing the factors that influence test parameters: compression ratio, power reduction and hardware overhead. To improve the compression ratio and the power reduction ratio, the proposed method is based on Modified Statistical Coding (MSC), Input Reduction (IR) scheme and the algorithms of reordering scan flip-flops and reordering test pattern sequence in a preprocessing step. Unlike previous approaches using the CSR architecture, the proposed method is to compress original test data, not $T_{diff}$, and decompress the compressed test data without the CSR architecture. Therefore, the proposed method leads to better compression ratio with lower hardware overhead and lower power consumption than previous works. An experimental comparison on ISCAS '89 benchmark circuits validates the proposed method.

• Tuberculosis and Respiratory Diseases
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• v.48 no.5
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• pp.682-698
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• 2000

Glucocorticoid receptor (GR) functions as a suppressor of inflammation by inhibiting the expression of many cytokine genes activated by NF-${\kappa}B$. The goal of this study is to investigate the mechanism by which GR repress NF-${\kappa}B$ activation in lung epithelial cells. We used A549 and BEAS-2B lung epithelia! cell lines. Using Ig$G{\kappa}$-NF-${\kappa}B$ luciferase reporter gene construct, we found that dexamethasone significantly suppressed TNF-$\alpha$-induced NF-${\kappa}B$ activation and the overexpression of GR showed dose-dependent reduction of TNF-$\alpha$-induced NF-${\kappa}B$ activity in both cell lines. However, DNA binding of NF-${\kappa}B$ induced by TNF-$\alpha$ in electromobility shift assay was not inhibited by dexamethasone. Super shift assay with anti-p65 antibody demonstrated the existence of p65 in NF-${\kappa}B$ complex induced by $\alpha$ Western blot showed that $I{\kappa}B{\alpha}$ degradation induced by TNF-$\alpha$ was not affected by dexamethasone and $I{\kappa}B{\kappa}$ was not induced by dexamethasone, neither. To evaluate p65 specific transactivation, we adopted co-transfection study of Gal4-p65TA1 or TA2 fusion protein expression system together with 5xGal4-luciferase vector. Co-transfection of GR with Gal4-p65TA1 or TA2 repressed luciferase activity profoundly to the level of 10-20% of p65TA1- or TA2-induced transcriptional activity. And this transrepressional effect was abolished by co-transfection of CBP of SRC-1 expression vectors. These results suggest that GR-mediated transrepression of NF-${\kappa}B$ in lung epithelial cells is through competing for binding to limiting amounts of transcriptional coactivators, CBP or SRC-1.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.794-806
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• 2017

It is essential to protect the national space assets and space environment safely as a space development country from the continuously increasing space debris. And Active Debris Removal(ADR) is the most active way to solve this problem. In this paper, we studied the Artificial Neural Network(ANN) for a stable recognition model of vision-based space debris tracking system. We obtained the simulated image of the space environment by the KARICAT which is the ground-based space debris clearing satellite testbed developed by the Korea Aerospace Research Institute, and created the vector which encodes structure and color-based features of each object after image segmentation by depth discontinuity. The Feature Vector consists of 3D surface area, principle vector of point cloud, 2D shape and color information. We designed artificial neural network model based on the separated Feature Vector. In order to improve the performance of the artificial neural network, the model is divided according to the categories of the input feature vectors, and the ensemble technique is applied to each model. As a result, we confirmed the performance improvement of recognition model by ensemble technique.

• Atmosphere
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• v.24 no.1
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• pp.49-68
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• 2014

This study analyzed atmospheric conditions for the convergent cloud band (Cu-Cb line) in developing stage and its neighbouring convections formed over the East Sea on 1 February 2012, by using synoptic, satellites data, and WRF numerical simulation output of high resolution. In both satellite images and the WRF numerical simulation outputs, the Cu-Cb line that stretched out toward northwest-southeast was shown in the East Sea, and cloud lines of the L mode were aligned in accordance with the prevailing surface wind direction. However, those of the T mode were aligned in the direction of NE-SW, which was nearly perpendicular direction to the surface winds. The directions of the wind shear vectors connecting top winds and bottom winds of the moist layers of the L mode and the T mode were identical with those of the cloud lines of L mode and T mode, respectively. From the WRF simulation convection circulations with a convergence in the lower layer of atmosphere and a divergence above 1.5 km ASL (Above Sea Level) were identified in the Cu-Cb line. A series of small sized vortexes (maximum vortex: $320{\times}10^{-5}s^{-1}$) of meso-${\gamma}$-scale formed by convergences was found along the Cu-Cb lines, suggesting that Cu-Cb lines, consisting of numerous convective clouds, were closely associated with a series of the small vortexes. There was an absolute unstable layer (${\partial}{\theta}/{\partial}z$ < 0) between sfc and ~0.3 km ASL, and a stable layer (${\partial}{\theta}/{\partial}z$ > 0) above ~2 km ASL over the Cu-Cb line and cloud zones. Not only convectively unstable layers (${\partial}{\theta}_e/{\partial}z$ < 0) but also neutral layers (${\partial}{\theta}_e/{\partial}z{\approx}=0$) in the lower atmosphere (sfc~1.5 km ASL) were scattered around over the cloud zones. Particularly, for the Cu-Cb line there were convectively unstable layers in the surface layer, and neutral layers (${\partial}{\theta}_e/{\partial}z{\approx}=0$) between 0.2 and ~1.5 km ASL over near the center of the Cu-Cb line, and the neutralization of unstable layers came from the release of convective instability.