• 제목/요약/키워드: Image Optimization

검색결과 728건 처리시간 0.023초

수정된 비용함수를 이용한 비선형 최적화 방법 기반의 이동로봇의 장애물 회피 비주얼 서보잉 (Visual Servoing of a Wheeled Mobile Robot with the Obstacle Avoidance based on the Nonlinear Optimization using the Modified Cost Function)

  • 김곤우
    • 전기학회논문지
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    • 제58권12호
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    • pp.2498-2504
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    • 2009
  • The fundamental research for the mobile robot navigation using the numerical optimization method is presented. We propose an image-based visual servo navigation algorithm for a wheeled mobile robot utilizing a ceiling mounted camera. For the image-based visual servoing, we define the composite image Jacobian which represents the relationship between the speed of wheels of a mobile robot and the robot's overall speed in the image plane. The rotational speed of wheels of a mobile robot can be directly related to the overall speed of a mobile robot in the image plane using the composite image Jacobian. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the cost function with the image error between the goal position and the position of a mobile robot. In order to avoid the obstacle, the modified cost function is proposed which is composed of the image error between the position of a mobile robot and the goal position and the distance between the position of a mobile robot and the position of the obstacle. The performance was evaluated using the simulation.

초점 연산자의 최적화를 통한 세포영상의 삼차원 형상 복원 알고리즘 (Shape From Focus Algorithm with Optimization of Focus Measure for Cell Image)

  • 이익현;최태선
    • 한국정보전자통신기술학회논문지
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    • 제3권3호
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    • pp.8-13
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    • 2010
  • Shape from focus (SFF) 방법은 이미지의 초점화된 영상을 이용하여 삼차원의 형상을 복원하는 방법이다. 그동안 많은 SFF 방법들이 연구되어 왔지만 노이즈에 대한 문제점과 영상특성으로 인한 최적화되지 못한 문제점이 남아있었다. 그러므로 노이즈를 제거하기 위한 필터링과 최적화 알고리즘을 제안한다. 성능 평가를 위하여 통계적인 판별기준인 평균제곱근오차 (RMSE)와 상관관계 (correlation) 수치를 이용한다.

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PCA와 입자 군집 최적화 알고리즘을 이용한 얼굴이미지에서 특징선택에 관한 연구 (A Study on Feature Selection in Face Image Using Principal Component Analysis and Particle Swarm Optimization Algorithm)

  • 김웅기;오성권;김현기
    • 전기학회논문지
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    • 제58권12호
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    • pp.2511-2519
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    • 2009
  • In this paper, we introduce the methodological system design via feature selection using Principal Component Analysis and Particle Swarm Optimization algorithms. The overall methodological system design comes from three kinds of modules such as preprocessing module, feature extraction module, and recognition module. First, Histogram equalization enhance the quality of image by exploiting contrast effect based on the normalized function generated from histogram distribution values of 2D face image. Secondly, PCA extracts feature vectors to be used for face recognition by using eigenvalues and eigenvectors obtained from covariance matrix. Finally the feature selection for face recognition among the entire feature vectors is considered by means of the Particle Swarm Optimization. The optimized Polynomial-based Radial Basis Function Neural Networks are used to evaluate the face recognition performance. This study shows that the proposed methodological system design is effective to the analysis of preferred face recognition.

상호정보 최적화를 통한 영상정합 (Image Registration by Optimization of Mutual Information)

  • 홍헬렌;김명희
    • 정보처리학회논문지B
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    • 제8B권2호
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    • pp.155-163
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    • 2001
  • 본 논문에서는 다중 모달리티 영상으로부터 의미 있는 정보를 제공하기 위하여 상호정보 최적화를 통한 영상정합 방법을 제안한다. 본 방법은 두 영상이 기하학적으로 정합되면 상호정보가 최대화된다는 가정 하에 두 영상에서 대응되는 위치의 명암도간 통계적 의존관계나 정보중복성을 계산하는 상호정보를 통하여 영상간 변형관계를 추정함으로써 영상을 정합한다. 실험결과로는 뇌 컴퓨터단층촬영영상의 상호정보를 최적화한 정합결과와 가우시안형 잡음 첨가에 따른 정합 비교 결과를 제시한다. 본 방법은 기존 정합방법에서 사용하는 영상분할이나 특징점 추출에 의한 정합이 아닌 영상 자체 정보를 사용함으로써 사용자와의 상호작용이 불필요하며 정합의 정확도를 향상시킬 수 있고 잡음에도 견고하다.

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A Hybrid Bacterial Foraging Optimization Algorithm and a Radial Basic Function Network for Image Classification

  • Amghar, Yasmina Teldja;Fizazi, Hadria
    • Journal of Information Processing Systems
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    • 제13권2호
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    • pp.215-235
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    • 2017
  • Foraging is a biological process, where a bacterium moves to search for nutriments, and avoids harmful substances. This paper proposes a hybrid approach integrating the bacterial foraging optimization algorithm (BFOA) in a radial basis function neural network, applied to image classification, in order to improve the classification rate and the objective function value. At the beginning, the proposed approach is presented and described. Then its performance is studied with an accent on the variation of the number of bacteria in the population, the number of reproduction steps, the number of elimination-dispersal steps and the number of chemotactic steps of bacteria. By using various values of BFOA parameters, and after different tests, it is found that the proposed hybrid approach is very robust and efficient for several-image classification.

비선형 최소 자승법을 이용한 이동 로봇의 비주얼 서보 네비게이션 (Visual Servo Navigation of a Mobile Robot Using Nonlinear Least Squares Optimization for Large Residual)

  • 김곤우;남경태;이상무;손웅희
    • 로봇학회논문지
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    • 제2권4호
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    • pp.327-333
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    • 2007
  • We propose a navigation algorithm using image-based visual servoing utilizing a fixed camera. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the image error between the goal position and the position of a mobile robot. The residual function which is the image error between the position of a mobile robot and the goal position is generally large for this navigation problem. So, this navigation problem can be considered as the nonlinear least squares problem for the large residual case. For large residual, we propose a method to find the second-order term using the secant approximation method. The performance was evaluated using the simulation.

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A Common Bitmap Block Truncation Coding for Color Images Based on Binary Ant Colony Optimization

  • Li, Zhihong;Jin, Qiang;Chang, Chin-Chen;Liu, Li;Wang, Anhong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권5호
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    • pp.2326-2345
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    • 2016
  • For the compression of color images, a common bitmap usually is generated to replace the three individual bitmaps that originate from block truncation coding (BTC) of the R, G and B channels. However, common bitmaps generated by some traditional schemes are not the best possible because they do not consider the minimized distortion of the entire color image. In this paper, we propose a near-optimized common bitmap scheme for BTC using Binary Ant Colony Optimization (BACO), producing a BACO-BTC scheme. First, the color image is compressed by the BTC algorithm to get three individual bitmaps, and three pairs of quantization values for the R, G, and B channels. Second, a near-optimized common bitmap is generated with minimized distortion of the entire color image based on the idea of BACO. Finally, the color image is reconstructed easily by the corresponding quantization values according to the common bitmap. The experimental results confirmed that reconstructed image of the proposed scheme has better visual quality and less computational complexity than the referenced schemes.

손 떨림 방지를 위한 OIS 액추에이터의 설계 (Design of Optical Image Stabilization Actuator for Compensating Hand Tremble)

  • 허영준;박노철;박영필;박경수
    • 정보저장시스템학회논문집
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    • 제7권2호
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    • pp.75-79
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    • 2011
  • Recently mobile phone camera become generally spread, it is required to develop high resolution, multi-functional camera module for obtaining high image quality. To satisfy this demand, number of pixels has been increased and pixel size decreased in small mobile phone cameras. As a result, image quality is seriously dropped by blur phenomena. Especially when hand tremble is occurred, image quality is dropped by camera shake. Therefore, to obtain high quality image, it is necessary to compensate user's hand tremble. In this paper, we propose voice coil actuator for compensating hand tremble, which can apply optical image stabilization (OIS) system. Sensitivity analysis and size optimization are performed to obtain high driving force. Finally, it is confirmed that the optimized electromagnetic circuit can be applied in OIS system.

영상 검색 시스템을 위한 다해상도 영상 검색 브라우징 방법과 최적화 (Multiresolution Image Browsing Techniques and Optimization for Image Retrieval System)

  • 박대철
    • 방송공학회논문지
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    • 제1권2호
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    • pp.96-107
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    • 1996
  • 영상 검색 시스템에서 공유망이나 저속 링크망 같은 통신망을 사용해 영상 DB를 조회하여 목표 영상을 결정하려는 경우 고화질 영상을 전송하게 되는 경우 전송 지연과 같은 문제점을 극복하기 힘들다. 본 논문에서는 다해상도의 영상 표현과 점진적 전송 방법을 통해 영상 검색 시스템의 성능 향상을 위한 브라우징 방법과 최적화 방법을 제안하였다. 제안된 통계적 모델 분석과 성능에 대하여 모의 실험을 통하여 성능 평가를 수행하였다. 여러 중간 해상도 계층을 사용하는 사용자-시스템간 대화형에 의한 검색 시스템은 단일 하위 계층을 사용하는 것보다 전송 지연 시간 측면의 큰 이득을 얻을 수 있음을 보였다.

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Image Quality Evaluation and Tolerance Analysis for Camera Lenses with Diffractive Element

  • Lee, Sang-Hyuck;Jeong, Ho-Seop;Jin, Young-Su;Song, Seok-Ho;Park, Woo-Je
    • Journal of the Optical Society of Korea
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    • 제10권3호
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    • pp.105-111
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    • 2006
  • A novel image quality evaluation method, which is based on combination of the rigorous grating diffraction theory and the ray-optic method, is proposed. It is applied for design optimization and, tolerance analysis of optical imaging systems implementing diffractive optical elements (DOE). The evaluation method can predict the quality and resolution of the image on the image sensor plane through the optical imaging system. Especially, we can simulate the effect of diffraction efficiencies of DOE in the camera lenses module, which is very effective for predicting different color sense and MTF performance. Using this method, we can effectively determine the fabrication tolerances of diffractive and refractive optical elements such as the variations' in profile thickness, and the shoulder of the DOE, as well as conventional parameters such as decenter and tilt in optical-surface alignments. A DOE-based 2M-resolution camera lens module designed by the optimization process based on the proposed image quality evaluation method shows ${\sim}15%$ MTF improvement compared with a design without such an optimization.