• Title/Summary/Keyword: a ill-conditioned process

Search Result 12, Processing Time 0.028 seconds

악조건하의 비동일평면 카메라 교정을 위한 알고리즘

  • Ahn, Taek-Jin;Lee, Moon-Kyu
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.7 no.12
    • /
    • pp.1001-1008
    • /
    • 2001
  • This paper presents a new camera calibration algorithm for ill-conditioned cases in which the camera plane is nearly parallel to a set of non-coplanar calibration boards. for the ill-conditioned case, most of existing calibration approaches such as Tsais radial-alignment-constraint method cannot be applied. Recently, for the ill-conditioned coplanar calibration Lee&Lee[16] proposed an iterative algorithm based on the least square method. The non-coplanar calibration algorithm presented in this paper is an iterative two-stage procedure with extends the previous coplanar calibration algorithm. Through the first stage, camera, position and orientation parameters as well as one radial distortion factor are determined optimally for a given data of the scale factor and the focal length. In the second stage, the scale factor and the focal length are locally optimized. This process is repeated until any improvement cannot be expected any more Computational results are provided to show the performance of the algorithm developed.

  • PDF

On the ill - condition of reverse process from structural dynamic response data (구조계의 동적응답을 이용한 역해석에서의 악조건)

  • 양경택
    • Proceedings of the Computational Structural Engineering Institute Conference
    • /
    • 1998.04a
    • /
    • pp.390-397
    • /
    • 1998
  • An approach to identifying input forces is proposed using measured structural dynamic responses and its analytical model. The identification of input forces is a reverse process and ill-conditioned problem. Its solution is unstable and generally case dependent. In this paper, the ill-condition is described considering characteristic matrix which is defined by reduced dynamic stiffness matrix. Special attention is focused on the condition number of a characteristic matrix used in the solution algorithm of this reverse process. Simple example is presented in support of the ill-condition of a reverse process.

  • PDF

Iterative identification methods for ill-conditioned processes

  • Lee, Jietae;Cho, Wonhui;Edgar, Thomas F.
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 1997.10a
    • /
    • pp.1762-1765
    • /
    • 1997
  • Some ill-conditioned processes are very sensitive to small element-wise uncertainties arising in classical element-by-element model identifications. For such processes, accurate identification of simgular values and right singular vectors are more important than theose of the elements themselves. Singular values and right singular vectors can be found by iteraive identification methods which implement the input and output transformations iteratively. Methods based on SVD decomposition, QR decomposition and LU decomposition are proposed and compared with the Kuong and Mac Gregor's method. Convergence proofs are given. These SVD and QR mehtods use normal matrices for the transformations which cannot be calculated analytically in general and so they are hoard to apply to dynamic processes, whereas the LU method used simple analyitc transformations and can be directly applied to dynamic processes.

  • PDF

A Camera Calibration Algorithm for an Ill-Conditioned Case (악조건하의 카메라 교정을 위한 알고리즘)

  • Lee, Jung-Hwa;Lee, Moon-Kyu
    • Journal of the Korean Society for Precision Engineering
    • /
    • v.16 no.2 s.95
    • /
    • pp.164-175
    • /
    • 1999
  • If the camera plane is nearly parallel to the calibration board on which objects are defined, most of existing calibration approaches such as Tsai's radial-alignment-constraint method cannot be applied. Recently, for such an ill-conditioned case, Zhuang & Wu suggested the linear two-stage calibration algorithm assuming that the exact values of focal length and scale factor are known a priori. In this paper, we developed an iterative two-stage algorithm starts with initial guess fo the two parameters to determine the value of the others using Zhuang & Wu's method. In the second stage, the two parameters are locally optimized. This process is repeated until any improvement cannot be expected any more. The performance comparison between Zhuang & Wu's method and our algorithm shows the superiority of ours. Also included are the computational results for the effects of the distribution and the number of calibration points on the calibration performance.

  • PDF

Design of the Well-Conditioned Observer Using the Non-Normality Measure (비정규지표를 이용한 Well-Conditioned 관측기 설계)

  • Jung, Jong-Chul;Huh, Kun-Soo
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.26 no.6
    • /
    • pp.1114-1119
    • /
    • 2002
  • In this paper, the well-conditioned observer is designed to be insensitive to the ill-conditioning factors in transient and steady-state observer performance. A condition number based on 12-norm of the eigenvector matrix of the observer matrix has been proposed on a principal index in the observer performance. For the well-conditioned observer design, the non-normality measure and the observability condition of the observer matrix are utilized. The two constraints are specified into observer gain boundary region that guarantees a small condition number and a stable observer. The observer gain selected in this region guarantees a well-conditioned and observable property. In this study, this method is applied to the Luenberger observer and Kalman filters for small order systems. In designing Kalman filters, the ratio of the process noise covariance to the measurement noise covariance is a design parameter and its effect on the condition number is investigated.

Design of the Well-Conditioned Observer Using the Non-normality Measure (비정규지표를 이용한 Well-Conditioned 관측기 설계)

  • 정종철;허건수
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
    • /
    • 2001.10a
    • /
    • pp.313-318
    • /
    • 2001
  • In this paper, the well-conditioned observer is designed to be insensitive to the ill-conditioning factors in transient and steady-state observer performance. A condition number based on $L_2-norm$ of the eigenvector matrix of the observer matrix has been proposed on a principal index in the observer performance. For the well-conditioned observer design, the non-normality measure and the observability condition of the observer matrix are utilized. The two constraints are specified into observer gain boundary region that guarantees a small condition number and a stable observer. The observer gain selected in this region guarantees a well-conditioned and observable property. In this study, this method is applied to the Luenberger observer and Kalman filters. In designing Kalman filters for small order systems, the ratio of the process noise covariance to the measurement noise covariance is a design parameter and its effect on the condition number is investigated.

  • PDF

A 2-D Image Camera Calibration using a Mapping Approximation of Multi-Layer Perceptrons (다층퍼셉트론의 정합 근사화에 의한 2차원 영상의 카메라 오차보정)

  • 이문규;이정화
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.4 no.4
    • /
    • pp.487-493
    • /
    • 1998
  • Camera calibration is the process of determining the coordinate relationship between a camera image and its real world space. Accurate calibration of a camera is necessary for the applications that involve quantitative measurement of camera images. However, if the camera plane is parallel or near parallel to the calibration board on which 2 dimensional objects are defined(this is called "ill-conditioned"), existing solution procedures are not well applied. In this paper, we propose a neural network-based approach to camera calibration for 2D images formed by a mono-camera or a pair of cameras. Multi-layer perceptrons are developed to transform the coordinates of each image point to the world coordinates. The validity of the approach is tested with data points which cover the whole 2D space concerned. Experimental results for both mono-camera and stereo-camera cases indicate that the proposed approach is comparable to Tsai's method[8]. Especially for the stereo camera case, the approach works better than the Tsai's method as the angle between the camera optical axis and the Z-axis increases. Therefore, we believe the approach could be an alternative solution procedure for the ill -conditioned camera calibration.libration.

  • PDF

On-the-machine measurement of surface roughness in a surface grinding process (평면연삭 공정에서의 표면 거칠기 기상계측)

  • 김현수
    • Proceedings of the Korean Society of Precision Engineering Conference
    • /
    • 1996.04a
    • /
    • pp.232-236
    • /
    • 1996
  • This paper deals with an on-the-machine measurement method for roughness of ground surface by using flux ratio of scattered lights. A sensor and control unit is developed so as to e applied to surface grinding processes. The performance of the sensor is compared with that of stylus. The experimental investigation shows that not onlythe sensor has good performance as a surface roughness sensor but alsothe sensor is very useful for monitoring grinding condition in order to detect ill-conditioned grinding or dressing time.

  • PDF

A HYBRID METHOD FOR REGULARIZED STRUCTURED LINEAR TOTAL LEAST NORM

  • KWON SUNJOO
    • Journal of applied mathematics & informatics
    • /
    • v.18 no.1_2
    • /
    • pp.621-637
    • /
    • 2005
  • A hybrid method solving regularized structured linear total least norm (RSTLN) problems, which have highly ill-conditioned coefficient matrix with special structures, is suggested and analyzed. This scheme combining RSTLN algorithm and separation by parts guarantees the convergence of parameters and has an advantages in reducing the residual norm and relative error of solutions. Computational tests for problems arisen in signal processing and image formation process confirm that the presenting method is effective for more accurate solutions to (R)STLN problem than the (R)STLN algorithm.

An Identification Technique Based on Adaptive Radial Basis Function Network for an Electronic Odor Sensing System

  • Byun, Hyung-Gi
    • Journal of Sensor Science and Technology
    • /
    • v.20 no.3
    • /
    • pp.151-155
    • /
    • 2011
  • A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.