• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.75-83
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• 2007

A model based approach of tracking the limbs of a walking human subject is proposed in this paper. The tracking process begins by building a data base composed of conditional probabilities of motions between the limbs of a walking subject. With a suitable amount of video footage from various human subjects included in the database, a probabilistic model characterizing the relationships between motions of limbs is developed. The motion tracking of a test subject begins with identifying and tracking limbs from the surveillance video image using the edge and silhouette detection methods. When occlusion occurs in any of the limbs being tracked, the approach uses the probabilistic motion model in conjunction with the minimum cost based edge and silhouette tracking model to determine the motion of the limb occluded in the image. The method has shown promising results of tracking occluded limbs in the validation tests.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.5
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• pp.537-542
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• 2014

The three-dimensional (3-D) NAND flash structure with fully charge storage using edge fringing field effect is presented, and its programming characteristic is evaluated. We successfully confirmed that this structure using fringing field effect provides good program characteristics showing sufficient threshold voltage ($V_T$) margin by technology computer-aided design (TCAD) simulation. From the simulation results, we expect that program speed characteristics of proposed structure have competitive compared to other 3D NAND flash structure. Moreover, it is estimated that this structural feature using edge fringing field effect gives better design scalability compared to the conventional 3D NAND flash structures by scaling of the hole size for the vertical channel. As a result, the proposed structure is one of the candidates of Terabit 3D vertical NAND flash cell with lower bit cost and design scalability.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1090-1100
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• 2021

Recently, as indoor activities increase due to the spread of infectious diseases, the metaverse is attracting attention. Metaverse refers to content in which the virtual world and the real world are closely related, and its representative platform technology is VR(Virtual Reality). However, since VR hardware is difficult to access in terms of cost, the concept of streaming-based cloud VR has emerged. This study proposes a server configuration and deployment method in an edge network when metaverse content involving multiple users operates based on cloud VR. The proposed algorithm deploys the edge server in consideration of the network and computing resources and client location for cloud VR, which requires a high level of computing resources while at the same time is very sensitive to latency. Based on simulation, it is confirmed that the proposed algorithm can effectively reduce the total network traffic load regardless of the number of applications or the number of users through comparison with the existing deployment method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.46-54
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• 2008

Most commercial CCD/CMOS image sensors have CFA(Color Filter Array) where each pixel gathers light of a selective color to reduce the sensor size and cost. There are many algorithms proposed to reconstruct the original clolr image by adopting pettern recognition of regularization methods to name a few. However the resulting image still suffer from errors such as flase color, zipper effect. In this paper we propose an adaptive edge weight demosaicking algorithm that is based on POCS(Projection Onto Convex Sets) not only to improve the entire image's PSNR but also to reduce the edge region's errors that affect subjective image quality. As a result, the proposed algorithm reconstruct better quality images especially at the edge region.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4220-4225
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• 2022

Monte Carlo (MC) simulations are increasingly being used as an alternative or supplement to the gamma spectrometric method in determining the full energy peak efficiency (FEPE) necessary for radionuclide identification and quantification. The MC method is more advantageous than the experimental method in terms of both cost and time. Experimental calibration with standard sources is difficult, especially for specimens with unusually shaped geometries. However, with MC, efficiency values can be obtained by modeling the geometry as desired without using any calibration source. Modeling the detector with the correct parameters is critical in the MC method. These parameters given to the user by the manufacturer are especially the dimensions of the crystal and its front edge, the thickness of the dead layer, dimensions, and materials of the detector components. This study aimed to investigate the effect of the front edge geometry of the detector crystal on efficiency, so the effect of rounded and sharp modeled front edges on the FEPE was investigated for <300 keV with three different HPGe detectors in point and volume source geometries using PHITS MC code. All results showed that the crystal should be modeled as a rounded edge, especially for gamma-ray energies below 100 keV.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.93-96
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• 2000

In this paper, we present an improved novel interpolator that performs high quality interpolation on both synthetic and real world images. Its structure, which is based on a four directional linear predictor with equiripple windowed samples and phase matching equalizer, provides edge-directional data interpolation so that sharp and artifacts-free images are obtained at a reasonable computational cost.

• Journal of Korean Society for Quality Management
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• v.31 no.4
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• pp.1-18
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• 2003

Quality is a critical competitive factor in today's environment because of the impact of quality on costs and delivery. Many companies regard quality as a key concept of company strategy in order to achieve the competitive edge. Measuring and reporting quality cost is the first step in quality management program. The supposition of quality cost model is that investment in prevention activities will bring rewards from reduced failure costs, and that further investment in prevention activities will show profits from reduced appraisal costs. In this study, the degree of quality cost deviation is conceptualized. This means a deviation between the ideal and present ranking in the amounts of quality cost categories. This study analysed that the effect of its deviation on quality management activity and performance variables. However, there are no difference in these variables. The major reason is that most of companies are endeavoring for quality management but operating quality cost system unsystematically. The review against a prevention and appraisal activity is necessary.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.155-163
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• 1999

In this paper, we propose novel scene change detection and key frame selection techniques, which use two feature images, i.e., DC and edge images, extracted directly from MPEG compressed video. For fast edge image extraction. we suggest to utilize 5 lower AC coefficients of each DCT. Based on this scheme, we present another edge image extraction technique using AC prediction. Although the former is superior to the latter in terms of visual quality, both methods all can extract important edge features well. Simulation results indicate that scene changes such as cut. fades, and dissolves can be correctly detected by using the edge energy diagram obtained from edge images and histograms from DC images. In addition. we find that our edge images are comparable to those obtained in the spatial domain while keeping much lower computational cost. And based on HVS, a key frame of each scene can also be selected. In comparison with an existing method using optical flow. our scheme can select semantic key frames because we only use the above edge and DC images.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.154-163
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• 2014

In this paper, there is suggested a fast intra prediction mode decision method in HEVC. To reduce the number of candidates in rough mode decision (RMD) process and rate-distortion optimization (RDO) process, the edge information and relative RMD cost are utilized. The experiment results show that the proposed method reduces encoding run-time by 26.81% with a negligible coding loss of 0.79% BD-rate on average.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3239-3267
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• 2018

Image and video dehazing is a popular topic in the field of computer vision and digital image processing. A fast, optimized dehazing algorithm was recently proposed that enhances contrast and reduces flickering artifacts in a dehazed video sequence by minimizing a cost function that makes transmission values spatially and temporally coherent. However, its fixed-size block partitioning leads to block effects. The temporal cost function also suffers from the temporal non-coherence of newly appearing objects in a scene. Further, the weak edges in a hazy image are not addressed. Hence, a video dehazing algorithm based on well designed spectral clustering is proposed. To avoid block artifacts, the spectral clustering is customized to segment static scenes to ensure the same target has the same transmission value. Assuming that edge images dehazed with optimized transmission values have richer detail than before restoration, an edge intensity function is added to the spatial consistency cost model. Atmospheric light is estimated using a modified quadtree search. Different temporal transmission models are established for newly appearing objects, static backgrounds, and moving objects. The experimental results demonstrate that the new method provides higher dehazing quality and lower time complexity than the previous technique.