• Title/Summary/Keyword: Edge Computation

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Systematic Approach to The Extraction of Effective Region for Tongue Diagnosis (설진 유효 영역 추출의 시스템적 접근 방법)

  • Kim, Keun-Ho;Do, Jun-Hyeong;Ryu, Hyun-Hee;Kim, Jong-Yeol
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.6
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    • pp.123-131
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    • 2008
  • In Oriental medicine, the status of a tongue is the important indicator to diagnose the condition of one's health like the physiological and the clinicopathological changes of internal organs in a body. A tongue diagnosis is not only convenient but also non-invasive, and therefore widely used in Oriental medicine. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition a lot. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue region from a facial image captured and classifying tongue coating are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth are similar. The proposed method includes preprocessing, over-segmenting, detecting the edge with a local minimum over a shading area from the structure of a tongue, correcting local minima or detecting the edge with the greatest color difference, selecting one edge to correspond to a tongue shape, and smoothing edges, where preprocessing consists of down-sampling to reduce computation time, histogram equalization, and edge enhancement, which produces the region of a segmented tongue. Finally, the systematic procedure separated only a tongue region from a face image with a tongue, which was obtained from a digital tongue diagnosis system. Oriental medical doctors' evaluation for the results illustrated that the segmented region excluding a non-tongue region provides important information for the accurate diagnosis. The proposed method can be used for an objective and standardized diagnosis and for an u-Healthcare system.

Efficient Structure-Oriented Filter-Edge Preserving (SOF-EP) Method using the Corner Response (모서리 반응을 이용한 효과적인 Structure-Oriented Filter-Edge Preserving (SOF-EP) 기법)

  • Kim, Bona;Byun, Joongmoo;Seol, Soon Jee
    • Geophysics and Geophysical Exploration
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    • v.20 no.3
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    • pp.176-184
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    • 2017
  • To interpret the seismic image precisely, random noises should be suppressed and the continuity of the image should be enhanced by using the appropriate smoothing techniques. Structure-Oriented Filter-Edge Preserving (SOF-EP) technique is one of the methods, that have been actively researched and used until now, to efficiently smooth seismic data while preserving the continuity of signal. This technique is based on the principle that diffusion occurs from large amplitude to small one. In a continuous structure such as a horizontal layer, diffusion or smoothing is operated along the layer, thereby increasing the continuity of layers and eliminating random noise. In addition, diffusion or smoothing across boundaries at discontinuous structures such as faults can be avoided by employing the continuity decision factor. Accordingly, the precision of the smoothing technique can be improved. However, in the case of the structure-oriented semblance technique, which has been used to calculate the continuity factor, it takes lots of time depending on the size of the filter and data. In this study, we first implemented the SOF-EP method and confirmed its effectiveness by applying it step by step to the field data. Next, we proposed and applied the corner response method which can efficiently calculate the continuity decision factor instead of structure-oriented semblance. As a result, we could confirm that the computation time can be reduced by about 6,000 times or more by applying the corner response method.

Fast Hough circle detection using motion in video frames (동영상에서 움직임을 이용한 빠른 허프 원 찾기)

  • Won, Hye-Min;Lee, Kyoung-Mi
    • Journal of Internet Computing and Services
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    • v.11 no.6
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    • pp.31-39
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    • 2010
  • The Generalized Hough Transform(GHT) is the most used algorithm for circle detection with high accuracy. However, it requires many computation time, because many different templates are applied in order to find circles of various size. In the case of circle detection and tracking in video, the classical approach applies GHT for each frame in video and thus needs much high processing time for all frames. This paper proposes the fast GHT algorithm in video, using two consecutive frames are similar. In the proposed algorithm, a change-driven method conducts GHT only when two consecutive frames have many changes, and trajectory-based method does GHT in candidate areas and with candidate radius using circles detected in a previous frame. The algorithm can reduce computation time by reducing the number of frames, the edge count, and the number of searching circles, as factors which affects the speed of GHT. Our experimental results show that the algorithm successfully detects circles with less processing time and no loss of accuracy in video acquisited by a fixed camera and a moving camera.

Fast 3D Model Extraction Algorithm with an Enhanced PBIL of Preserving Depth Consistency (깊이 일관성을 보존하는 향상된 개체군기반 증가 학습을 이용한 고속 3차원 모델 추출 기법)

  • 이행석;장명호;한규필
    • Journal of KIISE:Computer Systems and Theory
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    • v.31 no.1_2
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    • pp.59-66
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    • 2004
  • In this paper, a fast 3D model extraction algorithm with an enhanced PBIL of preserving depth consistency is proposed for the extraction of 3D depth information from 2D images. Evolutionary computation algorithms are efficient search methods based on natural selection and population genetics. 2D disparity maps acquired by conventional matching algorithms do not match well with the original image profile in disparity edge regions because of the loss of fine and precise information in the regions. Therefore, in order to decrease the imprecision of disparity values and increase the quality of matching, a compact genetic algorithm is adapted for matching environments, and the adaptive window, which is controlled by the complexity of neighbor disparities in an abrupt disparity point is used. As the result, the proposed algorithm showed more correct and precise disparities were obtained than those by conventional matching methods with relaxation scheme.

FPGA Implementation of Extreme Contour Point Algorithm to detect rotated angle of High Definition Image (고해상 영상의 회전된 각도를 검출하기 위한 Extreme Contour Point 알고리즘의 FPGA 설계)

  • Jeong, Min-woo;Pack, Chan-su;Kim, Hi-Seok
    • Journal of IKEEE
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    • v.20 no.4
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    • pp.344-350
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    • 2016
  • In this Paper, we propose an optimized method of hardware design based on Field Programmable Gate Array (FPGA) to detect rotated angle of high definition image about Extreme Contour Point (ECP) algorithm with moving video image could be not happened to translation motion, but also physical rotation motion. It was evaluated by XC7Z020 xc7z020-3clg400 FPGA board by using xilinx 14.2 tool. The much well-known method, the Coordinate Rotation Digital Integrated Computation (CORDIC) is an algorithm to estimate rotated angle between point and point. Through the result both ECP and CORDIC, our proposed design are confirmed to have similar operating speed of about 4ns with CORDIC. However, it is verified to have high performance result in terms of the hardware cost, is much better than CORDIC with cost reduction of registers and Look Up Tables (LUTs) of 108% and 91%, respectively.

Modified Scan Line Based Generalized Symmetry Transform with Selectively Directional Attention (선택적 방향주의를 가지는 수정된 스캔라인 일반화 대칭 변환)

  • Kim, Dong-Su;Jin, Seong-Il
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.4
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    • pp.411-421
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    • 2001
  • The generalized symmetry transform evaluates symmetry without segmentation and extracts regions of interest in an image by combining locality and reflectional symmetry The demand that the symmetry transform be local is reflected by the distance weight function. When calculating large regions-of-interest, we should select a large standard deviation of distance weight function. But such a large standard deviation makes the execution time increase in the second power of r, which is a radius of search area. In this paper we propose modified scan line based GST with selectively directional attention to improve time complexity The symmetry map of our proposed GST is found to be very similar to that of the existing GST. However the computation time of the proposed GST increases linearly with respect to r because our proposed GST evaluates symmetry between a pair of edge pixels along the scan lines. The GST computation decreases considerably when the proposed GST is peformed with selectively directional attention in case of large r. Several experiments in this paper demonstrate the time efficiency and the usefulness of our proposed GST.

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A Motion Vector Re-Estimation Algorithm for Image Downscaling in Discrete Cosine Transform Domain (이산여현변환 공간에서의 영상 축소를 위한 움직임 벡터 재추정)

  • Kim, Woong-Hee;Oh, Seung-Kyun;Park, Hyun-Wook
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.5
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    • pp.494-503
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    • 2002
  • A motion vector re-estimation algorithm for image downscaling in discrete consine transform domain is presented. Kernel functions are difined using SAD (Aum of Absolute Difference) and edge information of a macroblock. The proposed method uses these kernel functions to re-estimate a new motion vector of the downscaled image. The motion vectors from the incoming bitstream of transcoder are reused to reduce computation burden of the block-matching motion estimation, and we also reuse the given motion vectors. Several experiments in this paper show that the computation efficiency and the PSNR (Peak Signal to Noise Ratio) and better than the previous methods.

Numerical Simulation of Unsteady Cavitation in a High-speed Water Jet

  • Peng, Guoyi;Okada, Kunihiro;Yang, Congxin;Oguma, Yasuyuki;Shimizu, Seiji
    • International Journal of Fluid Machinery and Systems
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    • v.9 no.1
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    • pp.66-74
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    • 2016
  • Concerning the numerical simulation of high-speed water jet with intensive cavitation this paper presents a practical compressible mixture flow method by coupling a simplified estimation of bubble cavitation and a compressible mixture flow computation. The mean flow of two-phase mixture is calculated by URANS for compressible fluid. The intensity of cavitation in a local field is evaluated by the volume fraction of gas phase varying with the mean flow, and the effect of cavitation on the flow turbulence is considered by applying a density correction to the evaluation of eddy viscosity. High-speed submerged water jets issuing from a sheathed sharp-edge orifice nozzle are treated when the cavitation number, ${\sigma}=0.1$, and the computation result is compared with experimental data The result reveals that cavitation occurs initially at the entrance of orifice and bubble cloud develops gradually while flowing downstream along the shear layer. Developed bubble cloud breaks up and then sheds downstream periodically near the sheath exit. The pattern of cavitation cloud shedding evaluated by simulation agrees experimental one, and the possibility to capture the unsteadily shedding of cavitation clouds is demonstrated. The decay of core velocity in cavitating jet is delayed greatly compared to that in no-activation jet, and the effect of the nozzle sheath is demonstrated.

Electronic properties of graphene nanoribbons with Stone-Wales defects using the tight-binding method

  • M.W. Chuan;S.Z. Lok;A. Hamzah;N.E. Alias;S. Mohamed Sultan;C.S. Lim;M.L.P Tan
    • Advances in nano research
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    • v.14 no.1
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    • pp.1-15
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    • 2023
  • Driven by the scaling down of transistor node technology, graphene became of interest to many researchers following the success of its fabrication as graphene nanoribbons (GNRs). However, during the fabrication of GNRs, it is not uncommon to have defects within the GNR structures. Scaling down node technology also changes the modelling approach from the classical Boltzmann transport equation to the quantum transport theory because the quantum confinement effects become significant at sub-10 nanometer dimensions. The aim of this study is to examine the effect of Stone-Wales defects on the electronic properties of GNRs using a tight-binding model, based on Non-Equilibrium Green's Function (NEGF) via numeric computation methods using MATLAB. Armchair and zigzag edge defects are also implemented in the GNR structures to mimic the practical fabrication process. Electronic properties of pristine and defected GNRs of various lengths and widths were computed, including their band structure and density of states (DOS). The results show that Stone-Wales defects cause fluctuation in the band structure and increase the bandgap values for both armchair GNRs (AGNRs) and zigzag GNRs (ZGNRs) at every simulated width. In addition, Stone-Wales defects reduce the numerical computation DOS for both AGNRs and ZGNRs. However, when the lengths of the structures increase with fixed widths, the effect of the Stone-Wales defects become less significant.

Task offloading scheme based on the DRL of Connected Home using MEC (MEC를 활용한 커넥티드 홈의 DRL 기반 태스크 오프로딩 기법)

  • Ducsun Lim;Kyu-Seek Sohn
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.6
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    • pp.61-67
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    • 2023
  • The rise of 5G and the proliferation of smart devices have underscored the significance of multi-access edge computing (MEC). Amidst this trend, interest in effectively processing computation-intensive and latency-sensitive applications has increased. This study investigated a novel task offloading strategy considering the probabilistic MEC environment to address these challenges. Initially, we considered the frequency of dynamic task requests and the unstable conditions of wireless channels to propose a method for minimizing vehicle power consumption and latency. Subsequently, our research delved into a deep reinforcement learning (DRL) based offloading technique, offering a way to achieve equilibrium between local computation and offloading transmission power. We analyzed the power consumption and queuing latency of vehicles using the deep deterministic policy gradient (DDPG) and deep Q-network (DQN) techniques. Finally, we derived and validated the optimal performance enhancement strategy in a vehicle based MEC environment.