Showing papers on "Centroid published in 1994"

Paintbrush stylus for capacitive touch sensor pad

Abstract: A proximity sensor system includes a touch-sensor pad with a sensor matrix array having a characteristic capacitance on horizontal and vertical conductors connected to sensor pads. The capacitance changes as a function of the proximity of an object or objects to the sensor matrix. The change in capacitance of each node in both the X and Y directions of the matrix due to the approach of an object is converted to a set of voltages in the X and Y directions. These voltages are processed by circuitry to develop electrical signals representative of the centroid of the profile of the object, i.e, its position in the X and Y dimensions. Noise reduction and background level setting techniques inherently available in the architecture are employed. A conductive paintbrush-type stylus is used to produce paint-like strokes on a display associated with the touch-sensor pad.

The formulation of quantum statistical mechanics based on the Feynman path centroid density. II. Dynamical properties

Abstract: The formulation of quantum dynamical time correlation functions is examined within the context of the path centroid variable in Feynman path integration. This study builds on the centroid‐based approach to equilibrium properties developed in the companion paper. The introduction of the centroid perspective into the calculation of real time position correlation functions is outlined and an intriguing quasiclassical role for the centroid variable in real time position correlation functions is identified. This quasiclassical perspective is developed in terms of general interaction potentials, and the computational effort in implementing the method should scale with the size of the system in the same fashion as a classical molecular dynamics calculation. The centroid‐based theory is also implemented in several different approaches to calculate general time correlation functions. The theoretical results are illustrated and tested by representative numerical applications.

The formulation of quantum statistical mechanics based on the Feynman path centroid density. IV. Algorithms for centroid molecular dynamics

Abstract: Numerical algorithms are developed for the centroid molecular dynamics (centroid MD) method to calculate dynamical time correlation functions for general many‐body quantum systems. Approaches based on the normal mode path integral molecular dynamics and staging path integral Monte Carlo methods are described to carry out a direct calculation of the force on the centroid variables in the centroid MD algorithm. A more efficient, but approximate, scheme to compute the centroid force is devised which is based on the locally optimized harmonic approximation for the centroid potential. The centroid MD equations in the latter method can be solved with the help of an iterative procedure or through extended Lagrangian dynamics. A third algorithm introduces an effective centroid pseudopotential to approximate the full many‐body centroid mean force potential by effective pairwise centroid interactions. Numerical simulations for both prototype models and more realistic many‐body systems are performed to explore the feasibility and limitations of each algorithm.

The formulation of quantum statistical mechanics based on the Feynman path centroid density. III. Phase space formalism and analysis of centroid molecular dynamics

Abstract: The formulation of quantum statistical mechanics based on the path centroid variable in Feynman path integration is generalized to a phase space perspective, thereby including the momentum as an independent dynamical variable. By virtue of this approach, operator averages and imaginary time correlation functions can be expressed in terms of an averaging over the multidimensional phase space centroid density. The imaginary time centroid‐constrained correlation function matrix for the phase space variables is then found to define the effective thermal width of the phase space centroid variable. These developments also make it possible to rigorously analyze the centroid molecular dynamics method for computing quantum dynamical time correlation functions. As a result, the centroid time correlation function as calculated from centroid molecular dynamics is shown to be a well‐defined approximation to the exact Kubo transformed position correlation function. This analysis thereby clarifies the underlying role of the equilibrium path centroid variable in the quantum dynamical position correlation function and provides a sound theoretical basis for the centroid molecular dynamics method.

The formulation of quantum statistical mechanics based on the Feynman path centroid density. 3: Phase space formalism and analysis of centroid molecular dynamics

Abstract: : The formulation of quantum statistical mechanics based on the path centroid variable in Feynman path integration is generalized to a phase space perspective, thereby including the momentum as an independent dynamical variable. By virtue of this approach, operator averages and imaginary time correlation functions can be expressed in terms of an averaging over the multidimensional phase space centroid density. The imaginary time centroid- constrained correlation function matrix for the phase space variables is then found to define the effective thermal width of the phase space centroid variable. These developments also make it possible to rigorously analyze the centroid molecular dynamics method for computing quantum dynamical time correlation functions. As a result, the centroid time correlation function as calculated from centroid molecular dynamics is shown to be a well-defined approximation to the exact Kubo transformed position correlation function. This analysis thereby clarifies the underlying role of the equilibrium path centroid variable in the quantum dynamical position correlation function and provides a sound theoretical basis for the centroid molecular dynamics method. Chemical dynamics, Computer simulation, Electrochemistry

K-means clustering in a low-dimensional Euclidean space

Abstract: A procedure is developed for clustering objects in a low-dimensional subspace of the column space of an objects by variables data matrix. The method is based on the K-means criterion and seeks the subspace that is maximally informative about the clustering structure in the data. In this low-dimensional representation, the objects, the variables and the cluster centroids are displayed jointly. The advantages of the new method are discussed, an efficient alternating least-squares algorithm is described, and the procedure is illustrated on some artificial data.

Ultrasonic diagnostic system

Abstract: PURPOSE: To automatically set a region of interest(ROI) suitable for the area of an atrium, etc., in an ultrasonic diagnostic system. CONSTITUTION: The contour point detecting part 42 of an automatic ROI setting part 40 detects the contour point of a bloodstream area along each ultrasonic beam of sector scan. A centroid coordinate arithmetic part 44 finds the centroid of contour point groups from the coordinates of detected contour points. A moment of inertia arithmetic part 46 performs the coordinate transformation of the coordinate of each contour point to a centroid coordinate system setting the centroid as an origin, and finds the moment of inertia and products of inertia of the contour point group around each coordinate axis. An inertia main spindle arithmetic part 48 finds the inclination of an inertia main spindle for the centroid coordinate system based on the moment of inertia and the products of inertia. A ROI arithmetic part 50 finds the inertia main spindle based on the inclination, and decides the length of the major axis and minor axis of an elliptical ROI from the coordinate of the contour point in the neighborhood of the inertia main spindle, and sets the ROI so as to align the major axis and the minor axis with each inertia main spindle.

Estimator for the random error in subpixel target location and its use in the bundle adjustment

Abstract: A CCD camera and frame store provide image data that are affected by a number of imperfect processes. However, most of these can be quantified or estimated. For instance, the quantization process of allocating integer values from 0 to 255 for the intensity level of each pixel has well-known statistical properties. This paper discusses how these can lead to an estimate of the precision of location of target image centroids. Two centroid algorithms are analyzed. The theory is tested against experimental and simulated data.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Evaluation of subpixel feature localization methods for precision measurement

Abstract: This paper provides a review of a number of subpixel estimators classified as moment based, local modelling and reconstruction. Three algorithms are described in detail, one from each class. In the first, the basic centroid method is generalized so that it is applicable to a wider class of problems and the general formulation is applied to develop a subpixel ridge estimator. The second algorithm is a restricted polynomial model and is developed based on the assumption that an edge profile remains invariant in a local neighborhood. The third algorithm uses Gaussian interpolation to perform local image reconstruction. Simulations are performed to measure the performance of these three algorithms under ideal and noisy conditions.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Using the shape-matching method to compute sea-surface velocities from AVHRR satellite images

Abstract: The idea of shape matching is applied to track edge features automatically in a pair of AVHRR IR satellite images. The centroid and radius weighted mean are chosen as shape-specific points of the edges in two sequential images. Through the correspondence of these two shape-specific points, the whole edge's properties of rotation, translation, and scaling could be obtained. Also, a better correspondence in the second image is chosen according to the similarity comparison. After that, the total velocities of the points in the pattern can be computed. Velocity components in normal and tangential directions for certain points on the edge are also computed through a simple trial-and-error procedure and vector decomposition. >

Object recognition by alignment using invariant projections of planar surfaces

Abstract: This paper presents an efficient and robust alignment algorithm for recognizing 3D objects. We first show that for features from planar surfaces which undergo linear transformations in space, there exists a class of transformations that yield projections invariant to the surface motions, up to rotations in the image field. To use this property in recognition, we propose a new alignment approach based on centroid alignment of corresponding feature groups built on these invariant projections of planar surfaces. This method uses only a single pair of 2D model and data pictures for recognizing a 3D object. Some results on natural pictures are given.

Analysis of errors in dimensional inspection based on active vision

Abstract: Spatial quantization error and displacement error are inherent in automated visual inspection. This kind of error introduces significant distortion and dimensional uncertainty in the inspection of a part. For example, centroid, area, perimeter, length, and orientation of parts are inspected by the vision inspection system. This paper discusses the effect of the spatial quantization error and the displacement error on the precision dimensional measurement of an edge segment of a 3D model. Probabilistic analysis in terms of the resolution of the image is developed for one dimensional and two dimensional quantization error. The mean and variance of these errors are derived. The position and orientation errors (displacement error) of the active vision sensor are assumed to be normally distributed. The probabilistic analysis utilizes these errors and the angle of the line projected on the image. Using this analysis, one can determine whether a given set of sensor setting parameters in an active system is suitable to obtain a desired accuracy for specific line segment dimensional measurements. In addition, based on this approach, one can determine sensor positions and viewing direction which meet the necessary range for tolerance and accuracy of inspection. These mechanisms are helpful for achieving effective, economic, and accurate active inspection.

Device for finding centroid coordinates of figures

Abstract: A device for finding the centroid coordinates of a figure that can calculate the centroid from a single time measurement of the figure and display the calculated centroid of the figure. The measuring device comprises a main body having a roller capable of running in a single direction and a measuring lever pivotably supported by the main body so as to be rotatable right or left from the running direction of main body on a horizontal plane. In the measuring device, the main body has a display and a calculating circuit. The tracer of the measuring lever traces the contour of the figure to measure the coordinates, areas, and lengths of the figure. At the same time, the calculating circuit computes the geometrical moments of areas successively and sums the geometrical moments of the areas. Finally, the calculating circuit divides the summed geometrical moment of the areas by an area of the figure to obtain the coordinates of the centroid of the figure. The display is showing the differences of the current coordinates of the measuring lever from the coordinates of the centroid of the figure.

Tracking of moving object

Abstract: PURPOSE: To track an object in a scene expressed as a series of image frames picked up by a camera to display on a display device by projecting the new position of the centroid of the object in a continuously occurring frame through the use of the moving vector of a new object. CONSTITUTION: In order to arranging and tracking the head of a user, a motion detector 16, a primary head locator 17, a head tracker 18 and a motion evaluating device 19. Then each frame is divided into the areas of uniform movement. The primary arrangement of the object is needed, it is provided with such many areas of a uniform movements and each consecutive frame, areas belonging to the object are found to be called a new object. The centroid of the object is tracked across the sequence of a frame by using the evaluated movement of the frame. The centroid of the new object is not used for the track of the object but a projected centroid is used for the tracking of the object.

Inclination detecting method for ic

Abstract: PURPOSE:To execute the inclination detection for positioning an IC at a high speed and with high accuracy by extracting only a pin part of the IC by an image processing, deriving a centroid of the pin part, and deriving the center of the IC from this centroid. CONSTITUTION:An IC image is inputted, expansion and contraction processings are performed to this input image by a prescribed number of times, the image to which this expansion and contraction processings are performed is binarized, and to this binarized image, the contraction and expansion processings are performed by a prescribed number of times and it is subjected to labeling, and from this labeling image, a prescribed number of labeling images having an area of a prescribed range are extracted, and the centroid of each extracted labeling image thereof is derived. That is, by connecting the centroids of the opposed pin parts, an intersection points is derived, and it becomes the center coordinate of the IC. By connecting the center of this IC and the centroid of the pin, and comparing them with the horizontal and the vertical directions of a camera image, an inclination angle theta is derived. Accordingly, an inclination correction of the IC, and other correction or measurement can be executed, an inclination and a position, etc., of the IC can be detected simply, and for instance, mounting to a board can be executed quickly.

Automatic tracking image pickup device

Abstract: PURPOSE: To improve the precision of object setting and operability by extracting an object part from video signals and performing control so as to let the object part be outputted at the approximate center of a reproducing screen based on a feature amount such as the centroid position on the screen of the extracted object CONSTITUTION: A tracking processing circuit 8 extracts the object part from the video signals signal-processed by a video signal processing circuit 6, obtains the centroid coordinate and outputs it to a control circuit 9 The control circuit 9 controls a universal head 2 corresponding to the centroid coordinate outputted by the tracking processing circuit 8 and a target object set by the switch 14 of an operation unit 11 is tracked Thus, the target object is set while monitoring it by the operation unit 11 and the tracking conditions of a video equipment are remotely confirmed even after starting automatic tracking Thus, this device with improved setting precision of a tracking target and operability is obtained COPYRIGHT: (C)1996,JPO

Three-dimensional information restoration device

Abstract: PURPOSE:To restore three-dimensional information from an optical flow including a noise with high accuracy CONSTITUTION:A rigid body motion extraction part 1 calculates the time series of translational speed and that of rotating speed of a material body included in a time series image from the image A rotary motion parameter calculation part 3 sets a motion system based on a set law of motion, and calculates the coefficient of the system from the time series of rotating speed, and calculates the time series of three Eulerian angles theta, psi, and phi representing the posture (azimuth) of the material body A translational motion parameter calculation part 4 sets an equation of motion by the set law of motion, and calculates the coefficient of the equation from the time series of translational speed and that of rotating speed and calculates the centroid position of the material body Thereby, it is possible to restore the centroid position and the posture of the material body

Fourier phase shift location estimation of unfocused optical point spread functions

Abstract: Many applications in machine vision require the subpixel evaluation of the position of the center of a patch in a sampled image. The usual technique of calculation relies on the ‘centroid’ method (CCM) but it has been recently shown that this method is very sensitive to additive perturbations of the signal (distortions, noise, DC-offset etc.). Another method (FPS) has been proposed which stems from the frequency dependence of the argument of the Fourier transform. It has been demonstrated in the case of a focused Airy pattern that such a method is performed better and is also largely immune to perturbations. The aim of this paper is to show from a computer simulation that the advantages of FPS over CCM still hold when dealing with ring patterns (internal oscillations) such as those involved in defocused point source images.

Medical image diagnostic system having contour extracting function

Abstract: PURPOSE:To extract a contour with high accuracy on a diagnostic image by constituting the system so that a user extracts contour point candidate data with respect to a second diagnostic image, based on data of a comparatively narrow range containing border line data of an object inputted manually on a first diagnostic image CONSTITUTION:The contour extracting operation of an MRI system is as below A centroid and a centroid corresponding point of a first and a second images, the radiating direction in which each of them becomes an origin, and a standard range and a reference range are calculated and set (S1-S10) Subsequently, a correlation is taken between each image data of the standard range and the reference range in every corresponding radiating direction, and a point on a second image corresponding to contour point of a first image is found to be a contour point candidate (S11) When a difference between the contour point and the contour point candidate is within an allowable range based on a characteristic of the object, the contour point candidate becomes the contour point on a second image (S12) Then, the contour point on a second image is connected by a tertiary spline interpolation and becomes border line data, and validity of the border line data is evaluated interactively by a user (S13, 14)

Motion compensation algorithm for arbitrary translation of CT objects

Abstract: This paper presents a compensation technique for mitigating the blurring and streak artifacts in CT images caused by object translation. In order to detect and quantify the errors caused by motions, we first establish a nonsensor-based means to measure the incompleteness of a projection data set. Furthermore, with in-plane ray cancellation scheme, we show that it is possible to locate the regional motions. We then derive an isotropic reference, called centroid, to align parallel projections. The same concept is applied to fan beam projections except that here we use two sets of fan beam centroid to guide the projection alignment: one obtained from the original projection data set and the other from a pilot projection set. The latter is the reprojection of an iteratively improved image reconstructed from the updated projections. The convergence rate of this algorithm is demonstrated through simulations with projections based on mathematical phantom and human subject.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A registration method for rigid objects without point matching

Abstract: A method for the registration of rigid objects by attracting objects to the desired posture by appropriate forces is described. Inputs are a group of three-dimensional coordinates of the points representing an object in the initial state and in the goal state. No information on point correspondence between the initial and the goal states is given. Firstly, the object is translated from the initial position so that its centroid coincides with one of the goal position. The difference in posture of the object is corrected by rotating round the centroid by the torque which attracts it to the goal posture. We demonstrate that repulsive forces to each point of the object from all points at the goal posture, whose magnitude is the square of the distance between the points, satisfactorily produces such torque.

The Surprising Viability of a Simple Alternate Estimation Procedure for the Construction of Large-Scale Structural Equation Measurement Models

Abstract: As part of developing a comprehensive strategy for structural equation model building and assessment, a large‐scale Monte Carlo study of 7,200 covariance matrices sampled from 36 population models was conducted. This study compared maximum likelihood with the much simpler centroid method for the confirmatory factor analysis of multiple‐indicator measurement models. Surprisingly, the contribution of maximum likelihood to model analysis is limited to formal evaluation of the model. No statistically discernible differences were obtained for the bias, standard errors, or mean squared error (MSE) of the estimated factor correlations, and empirically obtained maximum likelihood standard errors for the pattern coefficients were only slightly smaller than their centroid counterparts. Further supporting the recommendations of Anderson and Gerbing (1982), the considerably faster centroid method may have a useful role in the analysis of these models, particularly for the analysis of large models with 50 or more input variables. These results encourage the further development of a comprehensive research paradigm that exploits the relative strengths of both centroid and maximum likelihood as complementary estimation procedures along an integrated exploratory‐confirmatory continuum of model specification, revision, and formal evaluation.

Finite element mesh generating method

Abstract: PURPOSE:To generate a hexahedron mesh scarcely having a distortion against an arbitrary shape by dividing a tetrahedron element into four hexahedron elements and forming it as the hexahedron mesh of a non-structure grid of the whole model to be analyzed. CONSTITUTION:By a primary processing, a tetrahedron mesh (intermediate mesh) in which a three-dimensional model to be analyzed is divided into plural tetrahedron elements 1 is formed. By a subsequent secondary processing, each tetrahedron element 1 of this tetrahedron mesh is redivided into four hexahedron elements 2, 3, 4 and 5. In this secondary processing, with regard to each of faces A1, A2, A3 and A4 of four triangles of the tetrahedron consisting of the apexes P1, P2, P3 and P4, the center of each side and the centroids G1, G2, G3 and G4 are connected, and also, each centroid G1, G2, G3 and G4 and the centroid G of the tetrahedron element 1 are connected. In such a way, one tetrahedron is divided into four hexahedrons 2, 3, 4 and 5.

Pattern recognizing device

Abstract: PURPOSE:To attain pattern recognition having a high SN ratio by moving the position of either one of patterns and allowing the position of a detector to coincide with that of a point having high luminance CONSTITUTION:A Fourier-transformed image is obtained from plural patterns by the Fourier transformation and the Fourier transformation is applied to the Fourier-transformed image to obtain a correlation value When both the patterns as matching with each other, a point with high luminance appears symmetrically with 0-th order light in accordance with the intensity of a center original pattern Since a distance between the high luminance point and the position of the 0-th order light is proportional to the distance between both the patterns, the position of a detector 140b is allowed to coincide with that of the high luminance position by moving the position of either one of the patterns Namely a controller 410 finds out the centroid position of the + or -1st order light from the detection output of a detector 140a, moves an input picture and controls the picture so that the centroid position of the + or -1st order light is positioned on the center of the detector 140a Consequently the positions of the + or - primary light and detector 104b can be adjusted so as to coincide with each other

Image tracking system

Abstract: PURPOSE:To improve anti-jamming performance by providing means for calculating inner product of angular differential vector and output vector from an angular speed calculating means for each region of an image, thereby, making a target distinguishable from a decoy even if they are close to each other. CONSTITUTION:An imaging unit 1 is fixed to a servo base 2 and directs the optical axis in an arbitrary direction. An inner product calculating means 11 receives a decision result from a centroid evaluating means and calculates the inner product of an output vector from an angular speed calculating means 13 and a centroid vector outputted from a centroid measuring means 6 for every region and decided to be valid. A maximum value selecting means 12 selects a centroid vector for a region having maximum inner product and outputs the centroid vector thus selected. A prediction filter 7 predicts a next time target centroid vector basing on a centroid vector provided from the selecting means 12 and an attitude angular speed vector of fuselage provided from an angular speed sensor 4. Prediction results are fed to an evaluating means 8 where next time order is determined while furthermore the prediction results are fed to the base 2 which is then controlled to direct the imaging unit 1 toward a target.

Element arranging method

Abstract: PURPOSE:To provide an element arranging method which quickly obtains an optimum solution independently of two-element exchange. CONSTITUTION:In the case of element arrangement improvement of an arrangement problem of a matrix structure, network centroid determining processing 5 which determines the centroid position of a network, element movement position determining processing 6 which obtains vectors of each element to the centroid of the network by the terminal position and determines the movement position of the element in accordance with an average vector obtained by averaging these vectors with respect to the pertinent element, element order determining processing 7 which determines the order of elements in accordance with coordinate values of movement positions, and element position determining processing 8 which arranges elements in the element order and determines the element arrangement in a matrix structure, where elements don't overlap, in accordance with shapes of elements and the shape of the matrix structure in the initial arrangement are provided.

Automatic centroid position detector for long size suspended cargo

Abstract: PURPOSE:To accurately and automatically display a position of the centroid of a suspended cargo such as long size steel. CONSTITUTION:An automatic centroid position detector is composed of a stand 1 on which a long size suspended cargo 2 is loaded horizontally, the first load gauge 3 arranged on one end of the stand 1 so as to measure a load applied to an optional point (A) between the centroid (G) of the suspended cargo 2 and one end of the suspended cargo, the second load gauge 4 arranged on the other end of the stand 1 so as to measure a load applied to an optional point (B) between the centroid (G) of the suspended cargo 2 and the other end of the suspended cargo, a controller 5 having an operation means to carry out operation on a position of the centroid of the suspended cargo 2 according to a distance between the preset point (A) and the point (B) and a display machine 6 to display the position of the centroid of the suspened cargo 2 obtained by the operation of the controller 5.