• Title/Summary/Keyword: Weighted Input Edge

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Efficient Connection of Migration Routes with Their Weights Using EGOSST (EGOSST를 이용한 이동 경로의 가중치를 반영한 효과적 연결)

  • Kim, In-Bum
    • The KIPS Transactions:PartA
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    • v.18A no.5
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    • pp.215-224
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    • 2011
  • In this paper, a mechanism connecting all weighted migration routes with minimum cost with EGOSST is proposed. Weighted migration routes may be converted to weighted input edges considered as not only traces but also traffics or trip frequencies of moving object on communication lines, roads or railroads. Proposed mechanism can be used in more wide and practical area than mechanisms considering only moving object traces. In our experiments, edge number, maximum weight for input edges, and detail level for grid are used as input parameters. The mechanism made connection cost decrease average 1.07% and 0.43% comparing with the method using weight minimum spanning tree and weight steiner minimum tree respectively. When grid detail level is 0.1 and 0.001, while each execution time for a connecting solution increases average 97.02% and 2843.87% comparing with the method using weight minimum spanning tree, connecting cost decreases 0.86% and 1.13% respectively. This shows that by adjusting grid detail level, proposed mechanism might be well applied to the applications where designer must grant priority to reducing connecting cost or shortening execution time as well as that it can provide good solutions of connecting migration routes with weights.

Improved Edge Enhanced Error Diffusion Halftoning Using Local Mean and Spatial Variation (국부 평균과 공간 변화량을 이용한 개선된 에지 강조 오차확산법)

  • Kwak Nae-Joung
    • The Journal of the Korea Contents Association
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    • v.5 no.2
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    • pp.221-228
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    • 2005
  • The paper proposes the improved error diffusion halftoning system to enhance the edges using the spatial perceptual characteristics of the human visual system. The proposed method computes a spatial variation(SV), which is the difference between a pixel luminance and the average of its $3{\times}3$ neighborhood pixels' luminances weighted according to the spatial positioning. Information of edge enhancement(IEE) Is computed using the SV and the local average luminance. The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The performance of the proposed method is compared with conventional methods by measuring the edge correlation. The halftone images by using the proposed method show better quality due to the enhanced edge. And the detailed edge is preserved in the halftone images by using the proposed method.

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Face and Facial Feature Detection under Pose Variation of User Face for Human-Robot Interaction (인간-로봇 상호작용을 위한 자세가 변하는 사용자 얼굴검출 및 얼굴요소 위치추정)

  • Park Sung-Kee;Park Mignon;Lee Taigun
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.1
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    • pp.50-57
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    • 2005
  • We present a simple and effective method of face and facial feature detection under pose variation of user face in complex background for the human-robot interaction. Our approach is a flexible method that can be performed in both color and gray facial image and is also feasible for detecting facial features in quasi real-time. Based on the characteristics of the intensity of neighborhood area of facial features, new directional template for facial feature is defined. From applying this template to input facial image, novel edge-like blob map (EBM) with multiple intensity strengths is constructed. Regardless of color information of input image, using this map and conditions for facial characteristics, we show that the locations of face and its features - i.e., two eyes and a mouth-can be successfully estimated. Without the information of facial area boundary, final candidate face region is determined by both obtained locations of facial features and weighted correlation values with standard facial templates. Experimental results from many color images and well-known gray level face database images authorize the usefulness of proposed algorithm.

A Study on Facial Wrinkle Detection using Active Appearance Models (AAM을 이용한 얼굴 주름 검출에 관한 연구)

  • Lee, Sang-Bum;Kim, Tae-Mook
    • Journal of Digital Convergence
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    • v.12 no.7
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    • pp.239-245
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    • 2014
  • In this paper, a weighted value wrinkle detection method is suggested based on the analysis on the entire facial features such as face contour, face size, eyes and ears. Firstly, the main facial elements are detected with AAM method entirely from the input screen images. Such elements are mainly composed of shape-based and appearance methods. These are used for learning the facial model and for matching the face from new screen images based on the learned models. Secondly, the face and background are separated in the screen image. Four points with the biggest possibilities for wrinkling are selected from the face and high wrinkle weighted values are assigned to them. Finally, the wrinkles are detected by applying Canny edge algorithm for the interested points of weighted value. The suggested algorithm adopts various screen images for experiment. The experiments display the excellent results of face and wrinkle detection in the most of the screen images.

A Triple Residual Multiscale Fully Convolutional Network Model for Multimodal Infant Brain MRI Segmentation

  • Chen, Yunjie;Qin, Yuhang;Jin, Zilong;Fan, Zhiyong;Cai, Mao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.3
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    • pp.962-975
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    • 2020
  • The accurate segmentation of infant brain MR image into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is very important for early studying of brain growing patterns and morphological changes in neurodevelopmental disorders. Because of inherent myelination and maturation process, the WM and GM of babies (between 6 and 9 months of age) exhibit similar intensity levels in both T1-weighted (T1w) and T2-weighted (T2w) MR images in the isointense phase, which makes brain tissue segmentation very difficult. We propose a deep network architecture based on U-Net, called Triple Residual Multiscale Fully Convolutional Network (TRMFCN), whose structure exists three gates of input and inserts two blocks: residual multiscale block and concatenate block. We solved some difficulties and completed the segmentation task with the model. Our model outperforms the U-Net and some cutting-edge deep networks based on U-Net in evaluation of WM, GM and CSF. The data set we used for training and testing comes from iSeg-2017 challenge (http://iseg2017.web.unc.edu).

Closed-form Expressions for Optimal Transmission Power Achieving Weighted Sum-Rate Maximization in MIMO Systems (MIMO 시스템의 가중합 전송률 최대화를 위한 최적 전송 전력의 닫힌 형태 표현)

  • Shin, Suk-Ho;Kim, Jae-Won;Park, Jong-Hyun;Sung, Won-Jin
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.47 no.7
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    • pp.36-44
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    • 2010
  • When multi-user MIMO (Multiple-Input Multiple-Output) systems utilize a sum-rate maximization (SRM) scheduler, the throughput of the systems can be enhanced. However, fairness problems may arise because users located near cell edge or experiencing poor channel conditions are less likely to be selected by the SRM scheduler. In this paper, a weighted sum-rate maximization (WSRM) scheduler is used to enhance the fairness performance of the MIMO systems. Closed-form expressions for the optimal transmit power allocation of WSRM and corresponding weighted sum-rate (WSR) are derived in the 6-sector collaborative transmission system. Using the derived results, we propose an algorithm which searches the optimal power allocation for WSRM in the 3-sector collaborative transmission system. Based on the derived closed-form expressions and the proposed algorithm, we perform computer simulations to compare performance of the WSRM scheduler and the SRM scheduler with respect to the sum-rate and the log-sum-of-average rates. We further verify that the WSRM scheduler efficiently improves fairness performance by showing the enhanced performance of average transmission rates in low percentile region.

The Error Diffusion halftoning Method Using Information of Edge Enhancement (에지 강조 정보를 이용한 오차확산 해프토닝)

  • Kwak Nae Joung;Ahn Jae Hyeong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.3 s.303
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    • pp.107-114
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    • 2005
  • Edge enhanced image is needed for processing images for special purpose such as a circuit diagram or a design composed of lines. Error diffusion halftoning, among digital halftoning methods to represent a continuous grayscale image for the binary output device such as printers, facsimiles, LCD televisions and etc. also makes edges of objects blurred. This paper proposes the method to enhance the edge of a binary image for the binary output device as well as a circuit diagram or a design. Based on that the human eyes perceive the local average luminance rather than the pixel's luminance itself, the proposed system uses a local activitymeasure (LAM), which is the difference between a pixel luminance and the average of its $3{\times}3$ neighborhood pixels' luminances weighted according to the spatial positioning. The system also usesinformation of edge enhancement(IEE), which is computed from the LAM multiplied by the average luminance. The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The simulation results show that the proposed method produces more fine halftoning images than conventional methods due to the enhanced edges. Also the performance of the proposed method is compared with that of the conventional method by measuring the edge correlation and the local average accordance over a range of viewing distances.

The Edge Detection of Image using the quantization FCNN with the variable template (가변 템플릿의 양자화 FCNN을 이용한 영상 에지 검출)

  • Choi, Seon-Kon;Byun, Oh-Sung;Lee, Cheul-Hee;Moon, Sung-Ryong
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.11
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    • pp.144-151
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    • 1998
  • In this paper, it is applied the analysis properties of mathematical morphology in order to process MIN/MAX operation on the basis of combination of predefined and weighted structuring element to FCNN having the structure of CNN combined with fuzzy logic between template and input/output. In this paper, as the fuzzy estimator is applied to the image including noise, thus it could be found the noise removal as well as the edge detection in the process of computer simulation. We could analyze and compare the results of edge detection using FCNN, CNN and median filter to which the erosion operation of morphology is applied. This paper could apply the static template and the variable template to FCNN using the quantization fuzzy function, in result we could confirm that the performance of FCNN got to improve in the process of computer simulation.

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An Improved Design Method of FIR Quadrature Mirror-Image Filter Banks (개선된 FIR QMF 뱅크의 설계 방법)

  • 조병모;김영수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.2C
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    • pp.213-221
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    • 2004
  • A new method for design of two-channel finite-impulse response(FIR) quadrature mirror-image filter(QMF) banks with low reconstruction delay using weighting function is proposed. The weighting function used in this paper is calculated from the previous updated filter coefficients vector which is adjusted from iteration to iteration in the design of QMF banks. In this paper, passband and stopband edge frequency are used in design of QMF banks with low delay characteristic in time domain instead of specific frequency interval where the artifacts occur in conventional design method. The investigation of specific frequency interval where artifacts occur can not be required by using passband and stopband edge frequency. Some comparisons of performance are made with other existing design method to demonstrate the proposed method for QMF bank design. and it was observed that the proposed method using the weighted function and passband and stopband edge frequency improves the peak reconstruction error by 0.001 [dB], the peak-to-peak passband ripple by 0.003[dB], SNR with a white noise by 7[dB] and SNR with a step input by 32[dB], but with a reduction of the computational efficiency because of updating the weighting function over the conventional method in Ref [11].

Edge-Enhanced Error Diffusion Halftoning using Local mean and Spatial Activity (국부 평균과 공간 활성도를 이용한 에지 강조 오차확산법)

  • Kwak Nae-Joung;Kwon Dong-Jin;Kim Young-Gil;Ahn Jae-Hyeong
    • The KIPS Transactions:PartB
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    • v.13B no.2 s.105
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    • pp.77-82
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    • 2006
  • Digital halftoning is the technique to obtain a bilevel-toned image from continuous-toned image. Among halftoning methods, the error diffusion method gives better subjective quality than other halftoning ones. But it also makes edges of objects blurred. To overcome the defect, we proposes the modified error diffusion to enhance the edges using the property that human vision perceives the local average luminance and doesn't perceive a little variation of the spatial variation. The proposed method computes a spatialactivity, which is the difference between a pixel luminance and the average of its $3{\times}3$ neighborhood pixels' Iuminance weighted according to the spatial positioning. The system also usesof edge enhancement (IEE), which is computed from the normalized spatial activitymultiplied by the average luminance. The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The computer experimental results show that the proposed method produces clearer bilevel-toned images than conventional methodsand the edge of objects is preserved well. Also the performance of the preposed method is improved, compared with that of the conventional method by measuring the edge correlation and the local average accordance at some ranges of viewing distance.