• Title/Summary/Keyword: ART2 algorithm

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Image Denoising via Fast and Fuzzy Non-local Means Algorithm

  • Lv, Junrui;Luo, Xuegang
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1108-1118
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    • 2019
  • Non-local means (NLM) algorithm is an effective and successful denoising method, but it is computationally heavy. To deal with this obstacle, we propose a novel NLM algorithm with fuzzy metric (FM-NLM) for image denoising in this paper. A new feature metric of visual features with fuzzy metric is utilized to measure the similarity between image pixels in the presence of Gaussian noise. Similarity measures of luminance and structure information are calculated using a fuzzy metric. A smooth kernel is constructed with the proposed fuzzy metric instead of the Gaussian weighted L2 norm kernel. The fuzzy metric and smooth kernel computationally simplify the NLM algorithm and avoid the filter parameters. Meanwhile, the proposed FM-NLM using visual structure preferably preserves the original undistorted image structures. The performance of the improved method is visually and quantitatively comparable with or better than that of the current state-of-the-art NLM-based denoising algorithms.

Enhanced Self Health Diagnosis Using ART2 Algorithm And fuzzy Logic (ART2 알고리즘과 퍼지 논리를 이용한 개선된 자가 진단 시스템)

  • Jang, Dea-Sung;Jang, Ho-Joong;Park, Choong-Shik;Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.386-393
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    • 2008
  • 시간이 부족한 현대인과 보살핌이 부족한 고령화 인구의 증가로 인해 비교적 가벼운 질병을 방치해 더 큰 고통을 겪는 경우가 발생하여 직접 병원에 가지 않고 자신의 건강 상태를 파악할 수 있는 시스템의 개발이 필요하게 되었다. 하지만 질병의 특성상, 증상의 차이와 구분에 의해 같은 질병이라도 다른 치료와 예방이 필요하고 다른 질병으로 세부 도출될 가능성이 있다. 따라서 증상의 차이를 고려하지 않고 단순한 증상의 선택만으로 도출된 결과는 상황을 더욱 악화시킬 가능성이 있다. 본 논문에서는 ART2 알고리즘을 이용하여 질병을 도출하고 증상의 차이를 구분하기 위해서 애매한 증상의 정도를 퍼지 소속 함수로 표현하고 퍼지 추론 방법을 적용하여 더욱더 정확한 질병 상세를 도출 할 수 있는 개선된 자가진단 시스템을 제시한다. 본 논문에서 제안한 방법을 전문의에게 분석을 의뢰한 결과, 본 논문에서 제안된 자가진단 시스템 방법이 이전의 방법보다, 지능형 자가 보조 진단 시스템으로서 사용자에게 더욱 효과적인 도움을 줄 수 있다는 가능성을 확인하였다.

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Dental Caries Extraction using YCbCr Color Model and ART2 Algorithm (YCbCr 색상모델과 ART2 알고리즘을 이용한 충치 추출)

  • Park, Ho-Jun;Kim, Yeon-Gyu;Lee, Sang-Geol;Cha, Eui-Young
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.1289-1291
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    • 2015
  • 본 논문에서는 충치 환자의 진단을 위해 구강 영상에서 충치를 추출하는 방법을 제안한다. 먼저 구강은 붉은색을 띄고 치아는 흰색을 띈다는 특징이 있기 때문에, 구강 영상을 YCbCr 컬러모델로 변환한다. YCbCr 컬러모델에 임계치를 설정하여 붉은 영역을 검출해내고, 검출된 붉은 영역에 대해 이진화하여 치아 영역을 추출한다. 그 후, 모폴로지 기법을 이용하여 잡음 제거 및 치아의 빈 공간을 채운다. 치아 영역 추출 시 영상에 따라 치아 사이를 잇는 모서리 부분이 손실된 경우가 발생할 수 있기 때문에 치아 사이의 손실된 부분을 연결 한다. 치아 영역에 ART2 알고리즘을 적용하여 클러스터링하고 충치 후보 영역을 추출한다. 충치 후보 영역에 8방향 윤곽선 추적 기법을 적용하여 충치를 분석 및 추출한다. 실험 결과 81%의 추출 성공률을 보였고 다양한 형태의 충치를 효과적으로 추출할 수 있는 것을 확인하였다.

Model-based fault diagnosis methodology using neural network and its application

  • Lee, In-Soo;Kim, Kwang-Tae;Cho, Won-Chul;Kim, Jung-Teak;Kim, Kyung-Youn;Lee, Yoon-Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.127.1-127
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    • 2001
  • In this paper we propose an input/output model based fault diagnosis method to detect and isolate single faults in the robot arm control system. The proposed algorithm is functionally composed of three main parts-parameter estimation, fault detection, and isolation, When a change in the system occurs, the errors between the system output and the estimated output cross a predetermined threshold, and once a fault in the system is detected, and in this zone the estimated parameters are transferred to the fault classifier by ART2(adaptive resonance theory 2) neural network for fault isolation. Since ART2 neural network is an unsupervised neural network fault classifier does not require the knowledge of all possible faults to isolate the faults occurred in the system. Simulations are carried out to evaluate the performance of the proposed ...

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Construction of 2D Image Mosaics Using Quasi-feature Point (유사 특징점을 이용한 모자이킹 영상의 구성)

  • Kim, Dae-Hyeon;Choe, Jong-Su
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.4
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    • pp.381-391
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    • 2001
  • This paper presents an efficient approach to build an image mosaics from image sequences. Unlike general panoramic stitching methods, which usually require some geometrical feature points or solve the iterative nonlinear equations, our algorithm can directly recover the 8-parameter planar perspective transforms. We use four quasi-feature points in order to compute the projective transform between two images. This feature is based on the graylevel distribution and defined in the overlap area between two images. Therefore the proposed algorithm can reduce the total amount of the computation. We also present an algorithm lot efficiently matching the correspondence of the extracted feature. The proposed algorithm is applied to various images to estimate its performance and. the simulation results present that our algorithm can find the correct correspondence and build an image mosaics.

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State of the Art Review of Shading Effects on PV Module Efficiencies and Their Detection Algorithm Focusing on Maximum Power Point

  • Lee, Duk Hwan;Lee, Kwang Ho
    • KIEAE Journal
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    • v.14 no.2
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    • pp.21-28
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    • 2014
  • This paper provides the up to date review of the shading effects on PV module performance and the associated detection algorithm related to the maximum power point tracking. It includes the brief explanations of the MMP variations due to the shading occurrence on the PV modules. Review of experimental and simulation studies highlighting the significant impacts of shading on PV efficiencies were presented. The literature indicates that even the partial shading of a single cell can greatly drop the entire module voltage and power efficiency. The MMP tracking approaches were also reviewed in this study. Both conventional and advanced soft computing methods such as ANN, FLC and EA were described for the proper tracking of MMP under shaded conditions. This paper would be the basic source and the comprehensive information associated with the shading effects and relevant MPP tracking technique.

Study on the Simultaneous Control of the Seam Tracking and Leg Length in a Horizontal Fillet Welding Part 2: Seam Tracking

  • Moon, H.S.;Na, S.J.
    • International Journal of Korean Welding Society
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    • v.1 no.1
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    • pp.31-38
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    • 2001
  • For the horizontal fillet welding with one plate in a vertical position, there will be a higher tendency of weld metal falling down rather than for the butt-welding in flat position. Such phenomenon could bring about the overlap or deflection of weld pool, and consequently induce the poor mechanical strength of weldments. Therefore, a precise position control of welding torch in conjunction with the weld qualify plays an important role in welding robot applications. In the present study, an experimental method was proposed for deriving a mathematical model between the leg length and the welding conditions. Finally, an algorithm was proposed for weld seam tracking and improvement of the weld quality. The reliability of the proposed algorithm was evaluated through various experiments, which showed that the proposed algorithm can be very effective for tracking the weld line and simultaneously achieving the sound weld bead.

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Part-Machine Grouping Using Production Data-based Part-Machine Incidence Matrix: Neural Network Approach - Part 2 (생산자료기반 부품-기계 행렬을 이용한 부품-기계 그룹핑 : 인공신경망 접근법 - Part 2)

  • Won, Yu-Gyeong
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.11a
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    • pp.656-658
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    • 2006
  • This study deals with the part-machine grouping (PMG) that considers realistic manufacturing factors, such as the machine duplication, operation sequences with multiple visits to the same machine, and production volumes of parts. Basically, this study is an extension of Won(2006) that has adopted fuzzy ART neural network to group parts and machines. The proposed fuzzy ART neural network algorithm is implemented with an ancillary procedure to enhance the block diagonal solution by rearranging the order of input presentation. Computational experiments applied to large-size PMG data sets with a psuedo-replicated clustering procedure show effectiveness of the proposed approach.

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Large-scale 3D fast Fourier transform computation on a GPU

  • Jaehong Lee;Duksu Kim
    • ETRI Journal
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    • v.45 no.6
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    • pp.1035-1045
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    • 2023
  • We propose a novel graphics processing unit (GPU) algorithm that can handle a large-scale 3D fast Fourier transform (i.e., 3D-FFT) problem whose data size is larger than the GPU's memory. A 1D FFT-based 3D-FFT computational approach is used to solve the limited device memory issue. Moreover, to reduce the communication overhead between the CPU and GPU, we propose a 3D data-transposition method that converts the target 1D vector into a contiguous memory layout and improves data transfer efficiency. The transposed data are communicated between the host and device memories efficiently through the pinned buffer and multiple streams. We apply our method to various large-scale benchmarks and compare its performance with the state-of-the-art multicore CPU FFT library (i.e., fastest Fourier transform in the West [FFTW]) and a prior GPU-based 3D-FFT algorithm. Our method achieves a higher performance (up to 2.89 times) than FFTW; it yields more performance gaps as the data size increases. The performance of the prior GPU algorithm decreases considerably in massive-scale problems, whereas our method's performance is stable.

ROI-Based 3D Video Stabilization Using Warping (관심영역 기반 와핑을 이용한 3D 동영상 안정화 기법)

  • Lee, Tae-Hwan;Song, Byung-Cheol
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.2
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    • pp.76-82
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    • 2012
  • As the portable camcorder becomes popular, various video stabilization algorithms for de-shaking of camera motion have been developed. In the past, most video stabilization algorithms were based on 2-dimensional camera motion, but recent algorithms show much better performance by considering 3-dimensional camera motion. Among the previous video stabilization algorithms, 3D video stabilization algorithm using content-preserving warps is known as the state-of-the art owing to its superior performance. But, the major demerit of the algorithm is its high computational complexity. So, we present a computationally light full-frame warping algorithm based on ROI (region-of-interest) while providing comparable visual quality to the state-of-the art in terms of ROI. First, a proper ROI with a target depth is chosen for each frame, and full-frame warping based on the selected ROI is applied.