• 제목/요약/키워드: Robust algorithm

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Check4Urine: Smartphone-based Portable Urine-analysis System (Check4Urine: 스마트폰 기반 휴대용 소변검사 시스템)

  • Cho, Jungjae;Yoo, Joonhyuk
    • IEMEK Journal of Embedded Systems and Applications
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    • 제10권1호
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    • pp.13-23
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    • 2015
  • Recently, a few image-processing based mobile urine testers have actively been studied since the urine-analysis result can be available to the user in real time immediately after the test is done. However, the accuracy of test result can be severely degraded due to variable illumination environments and a variety of manners to capture the image with a camera embedded in the smartphone according to different users. This paper proposes the Check4Urine system, a novel smartphone-based portable urine-analysis tester and provides three techniques to improve such a performance degradation problem robust to various test environments and disturbances, which are the compensation algorithm to correct the varying illumination effect, an urine strip detection algorithm robust to edge loss of the object image, and the color decision algorithm based on the pre-processed reference table. Experimental results show that the proposed Check4Urine system increases the accuracy of urine-analysis by 20-50% at various test conditions, compared with the existing image-processing based mobile urine tester.

Robust Object Extraction Algorithm in the Sea Environment (해양환경에서 강건한 물표 추적 알고리즘)

  • Park, Jiwon;Jeong, Jongmyeon
    • Journal of the Korean Institute of Intelligent Systems
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    • 제24권3호
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    • pp.298-303
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    • 2014
  • In this paper, we proposed a robust object extraction and tracking algorithm in the IR image sequence acquired in the sea environment. In order to extract size-invariant object, we detect horizontal and vertical edges by using DWT and combine it to generate saliency map. To extract object region, binarization technique is applied to saliency map. The correspondences between objects in consecutive frames are defined by the calculating minimum weighted Euclidean distance as a matching measure. Finally, object trajectories are determined by considering false correspondences such as entering object, vanishing objects and false object and so on. The proposed algorithm can find trajectories robustly, which has shown by experimental results.

Automatic Extraction of Lean Tissue for Pork Grading

  • Cho, Sung-Ho;Huan, Le Ngoc;Choi, Sun;Kim, Tae-Jung;Shin, Wu-Hyun;Hwang, Heon
    • Journal of Biosystems Engineering
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    • 제39권3호
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    • pp.174-183
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    • 2014
  • Purpose: A robust, efficient auto-grading computer vision system for meat carcasses is in high demand by researchers all over the world. In this paper, we discuss our study, in which we developed a system to speed up line processing and provide reliable results for pork grading, comparing the results of our algorithms with visual human subjectivity measurements. Methods: We differentiated fat and lean using an entropic correlation algorithm. We also developed a self-designed robust segmentation algorithm that successfully segmented several porkcut samples; this algorithm can help to eliminate the current issues associated with autothresholding. Results: In this study, we carefully considered the key step of autoextracting lean tissue. We introduced a self-proposed scheme and implemented it in over 200 pork-cut samples. The accuracy and computation time were acceptable, showing excellent potential for use in online commercial systems. Conclusions: This paper summarizes the main results reported in recent application studies, which include modifying and smoothing the lean area of pork-cut sections of commercial fresh pork by human experts for an auto-grading process. The developed algorithms were implemented in a prototype mobile processing unit, which can be implemented at the pork processing site.

Robust Adaptive Control System for Induction Motor Drive Without Speed Sensor at Low Speed (저속영역에서 속도검출기가 없는 유도전동기의 강인성 적응제어 시스템)

  • Kim, Min-Heui
    • Journal of the Korean Society of Industry Convergence
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    • 제2권2호
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    • pp.91-102
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    • 1999
  • The paper describes a robust adaptive control algorithm for induction motor drive without speed sensor at low speed range. The control algorithm use only current sensors in a space vector pulse width modulation within loop control with rotor speed estimation and voltage source inverter. On-line rotor speed estimation is based on utilizing parallel model reference adaptive control system. MRAC of the modified flux model for flux and rotor speed estimator uses dual-adaptation mechanism, ${\omega}_r$ and ${\omega}_e$ scheme. The estimated flux components in the model can be compensated from the effects of offset errors on pure integrals. It can be compensated to the parameter variations and torque fluctuation with speed estimation in less then 10 rad/sec. In a simulation, the proposed induction motor control algorithm without speed sensor at very low speed range are shown to operate very well in spite of variable rotor time constant and fluctuating load without change the controller parameters. The suggested control strategy and estimation method have been validated by simulation study, and it proposed the designed system for the implementation using TI320C31 DSP/ASIC controller.

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The Proposal of the Robust Fuzzy Wavelet Morphology Neural Networks Algorithm for Edge of Color Image (컬러 영상 에지에 강건한 퍼지 웨이브렛 형태학 신경망 알고리즘 제안)

  • Byun, Oh-Sung
    • Journal of the Korea Society of Computer and Information
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    • 제12권2호
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    • pp.53-62
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    • 2007
  • In this paper, it can propose that Fuzzy Wavelet Morphology Neural Networks for the edge detection algorithm with being robustly a unclear boundary parts by brightness difference and being less sensitivity on direction to be detected the edges of images. This is applying the Fuzzy Wavelet Morphology Operator which can be simple the image robustly without the loss of data to DTCNN Structure for improving defect which carrys out a lot of operation complexly. Also, this color image can segment Y image with YCbCr space color model which has a lossless feature information of edge boundary sides effectively. This paper can offer the simulation of color images of 50ea for the performance verification of the proposal algorithm.

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Efficient NLP Techniques for the Optimum Design of Simple Steel Plate Girder Cross Section (단순강판형 단면의 최적설계를 위한 효율적인 비선형계획기법)

  • 김종옥
    • Magazine of the Korean Society of Agricultural Engineers
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    • 제36권2호
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    • pp.111-122
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    • 1994
  • In this study, an algorithm which can be applied to the optimum design of simple steel plate girders was developed, and efficient optimization strategies for the solution of algorithm were found out. The optimum design algorithm consists of 3-levels of optimization. In the first and second levels of optimization, the absolute maximum bending moment and shearing force are extracted and in the third level of optimization, the optimum cross section of steel plate girder is determined. For the optimum design of cross section, the objective function is formulated as the total area of cross section and constraints are derived in consideration of the various stresses and the minimum dimension of flange and web based on the part of steel bridge in the Korea standard code of road bridge. Sequential unconstrained minimization technique using the exterior penalty function method(SUMT-EP), sequential linear programming(SLP) and sequential quadratic programming (SQP) are proved to be efficient and robust strategies for the optimum design of simple plate girder cross section. From the reliable point of view, SLP is the most efficient and robust strategy and SQP is the most efficient one from the viewpoint of converguency and computing time.

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A Method for Object Tracking Based on Background Stabilization (동적 비디오 기반 안정화 및 객체 추적 방법)

  • Jung, Hunjo;Lee, Dongeun
    • Journal of Korea Society of Digital Industry and Information Management
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    • 제14권1호
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    • pp.77-85
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    • 2018
  • This paper proposes a robust digital video stabilization algorithm to extract and track an object, which uses a phase correlation-based motion correction. The proposed video stabilization algorithm consists of background stabilization based on motion estimation and extraction of a moving object. The motion vectors can be estimated by calculating the phase correlation of a series of frames in the eight sub-images, which are located in the corner of the video. The global motion vector can be estimated and the image can be compensated by using the multiple local motions of sub-images. Through the calculations of the phase correlation, the motion of the background can be subtracted from the former frame and the compensated frame, which share the same background. The moving objects in the video can also be extracted. In this paper, calculating the phase correlation to track the robust motion vectors results in the compensation of vibrations, such as movement, rotation, expansion and the downsize of videos from all directions of the sub-images. Experimental results show that the proposed digital image stabilization algorithm can provide continuously stabilized videos and tracking object movements.

Robust video watermarking algorithm for H.264/AVC based on JND model

  • Zhang, Weiwei;Li, Xin;Zhang, Yuzhao;Zhang, Ru;Zheng, Lixin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권5호
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    • pp.2741-2761
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    • 2017
  • With the purpose of copyright protection for digital video, a novel H.264/AVC watermarking algorithm based on JND model is proposed. Firstly, according to the characteristics of human visual system, a new and more accurate JND model is proposed to determine watermark embedding strength by considering the luminance masking, contrast masking and spatial frequency sensitivity function. Secondly, a new embedding strategy for H.264/AVC watermarking is proposed based on an analysis on the drift error of energy distribution. We argue that more robustness can be achieved if watermarks are embedded in middle and high components of $4{\times}4$ integer DCT since these components are more stable than dc and low components when drift error occurs. Finally, according to different characteristics of middle and high components, the watermarks are embedded using different algorithms, respectively. Experimental results demonstrate that the proposed watermarking algorithm not only meets the imperceptibility and robustness requirements, but also has a high embedding capacity.

Realtime Robust Curved Lane Detection Algorithm using Gaussian Mixture Model (가우시안 혼합모델을 이용한 강인한 실시간 곡선차선 검출 알고리즘)

  • Jang, Chanhee;Lee, Sunju;Choi, Changbeom;Kim, Young-Keun
    • Journal of Institute of Control, Robotics and Systems
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    • 제22권1호
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    • pp.1-7
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    • 2016
  • ADAS (Advanced Driver Assistance Systems) requires not only real-time robust lane detection, both straight and curved, but also predicting upcoming steering direction by detecting the curvature of lanes. In this paper, a curvature lane detection algorithm is proposed to enhance the accuracy and detection rate based on using inverse perspective images and Gaussian Mixture Model (GMM) to segment the lanes from the background under various illumination condition. To increase the speed and accuracy of the lane detection, this paper used template matching, RANSAC and proposed post processing method. Through experiments, it is validated that the proposed algorithm can detect both straight and curved lanes as well as predicting the upcoming direction with 92.95% of detection accuracy and 50fps speed.

Network Jitter Estimation Algorithm for Robust VoIP System in Vehicle Environment (자동차 환경내 안정적인 VoIP 시스템을 위한 네트워크 지터 추정 알고리즘)

  • Seo, Kwang-Duk;Lee, Jin-Ho;Kim, Hyoung-Gook
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • 제10권4호
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    • pp.93-99
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    • 2011
  • This paper proposes a novel network jitter estimation algorithm for robust VoIP communication system. The proposed method computes the current network environment mode using the differences of arrival time and generation time from sequential received packets. According to the current network environment mode, the jitter variance weights is adjusted to minimize the error for estimating the network jitter. The jitter average and variance are calculated by the autoregressive estimated algorithm, and then the network jitter is estimated by applying the jitter variance weights.