Showing papers on "Centroid published in 1989"

On the detection of the axes of symmetry of symmetric and almost symmetric planar images

Abstract: A simple algorithm is presented for finding all the axes of symmetry of symmetric and almost symmetric planar images having nonuniform gray-level (intensity images). The technique, which can also be used in conjunction with planar curves, is based on the identification of the centroids of the given image and other related sets of points, followed by a maximization of a specially defined coefficient of symmetry. Owing to the nature of the required procedures, which are strictly based on the computation of mean values, the method is not particularly affected by the presence of noise and is especially suited for application in conjunction with digitized figures. >

Geometric precision in noise-free digital images

Abstract: A basis for determining the best possible precision for the position of a given object in a digital image is developed. The approach is general, being independent of object-form and providing a performance bound on all position estimation schemes. The central concepts in the development are the locale and total variation of the image function. An easily computed bound for the smallest attainable RSM position estimation error is developed. The best possible estimate is given by the centroids of the locales. The analysis of geometric precision using locales shows how object position-uncertainty depends on the object's position. Visual inspection of the easily generated locale pattern gives a qualitative impression of the spatial distribution of geometric precision. The analytic techniques developed provide avenues for both qualitative and quantitative evaluation of target forms and position estimation schemes in terms of their precision mensuration capabilities. >

Point pattern matching using centroid bounding

Abstract: A method is presented for matching point patterns A and B in the plane where mod A mod = mod B mod =N. The method is capable of determining the registration and matching and is not affected by translation, rotation, scaling or noise. An example application of the algorithm to the matching of flat parts is shown. The algorithm not only allows part recognition, but may also be extended to perform automated verification of the dimension of the part. >

The Metabolic Centroid Method for PET Brain Image Analysis

Abstract: The method of centroids is an approach to the analysis of three-dimensional whole-brain positron emission tomography (PET) metabolic images It utilizes the brain's geometric centroid and metabolic centroid so as to objectively characterize the central tendency of the distribution of metabolic activity in the brain The method characterizes the three-dimensional PET metabolic image in terms of four parameters: the coordinates of the metabolic centroid and the mean metabolic rate of the whole brain These parameters are not sensitive to spatially uniform random noise or to the position of the subject's head within a uniform PET camera field of view The method has been applied to 40 normal subjects, 22 schizophrenics who were treated with neuroleptics, and 20 schizophrenics who were neuroleptic-free The mean metabolic centroid of the normal subjects was found to be superior to the mean geometric centroid of the brain The mean metabolic centroid of chronic schizophrenics is lower and more posterior to the

Apparatus for identification and tracking of objects

Abstract: Target acquisition device with an imaging sensor, a signal processing circuit and an evaluating circuit comprising a computer for implementing a gray-value analysis of the output signals of the imaging sensor, wherein the signal processing circuit contains threshold value transmitters for the brightness transitions and for the local extreme values, a selection of three values, bright/reference/dark, is effected in the signal evaluation circuit and a centroid of the target is determined from the latter, particularly by means of producing coordinates of the target, and, in order to acquire the target according to the position finding by means of comparison of the measured parameters with the stored parameters in the evaluating circuit, the computer also evaluates the mathematical signs of the received gradient image for determining the target direction, and in that, in addition to a binary image, edges and non-edges, edge points lying on a straight line can also be obtained, particularly from one or more image sections.

A VLSI Centroid Extractor For Real-Time Target Tracking Applications

Abstract: The Automatic Centroid Extractor (ACE) is a CMOS VLSI chip that per-forms target extraction and centroiding functions for an extensible real-time target tracking system. Contiguous pixels whose intensities exceed a given threshold are grouped into separate objects, and three weighted sums of pixel intensities that can rapidly be converted to the target centroid and average intensity are calculated for each object. Proper assignment of contiguous pixels to their respective objects is guaranteed for all convex shapes and most concave shapes. Data for a NxM pixel image is processed in raster scan format with a maximum value of 1024 for N and M. ACE can process in excess of 500 objects per frame and accepts input at up to 20 Megapixels per second. To increase the flexibility of the chip, arbitrary circular regions of the image can be masked so that they do not enter the target extraction process. This allows any set of fixed targets to be ignored if they are not of interest. The chip is a full custom design containing approximately 200,000 transistors and is being fabricated using Hewlett Packard's CMOS40 process. The ACE chip interfaces directly to the Inmos Transputer over a serial link. The communication link is used to select the threshold and to specify the circular regions of the image that will be masked, as well as to transfer target centroids and status information.

Identification of sheet paper

Abstract: PURPOSE: To highly accurately perform discrimination by obtaining a detection value relating to a pattern by plural detectors arranged in a direction perpendicualr to a carrying direction, obtaining a centroid value perpendicular to the carrying direction from the detection value for each detection area and checking whether or not a centroid group and a detection group are within an allowable range. CONSTITUTION: A control part 7 is provided with a ROM 21, a RAM 22 and a microcomputer 23. Then, a procedure for controlling a discrimination device is stored in the ROM 21 and the respective kinds of information and numerical values in the procedure of the control are stored in the RAM 22. Then, the RAM 22 stores the detection value in the detection area arranged in the direction perpendicular to the carrying direction. The centroid value perpendicular to the carrying direction is obtained by an arithmetic operation from the detection value for each detection area and whether or not the centroid group and the detection group are within the allowable range is judged. By judging excellent in the case of being within the allowable range as a result, the highly accurate discrimination is performed.

Extraction and optimal use of measurements from an imaging sensor for precision target tracking

Abstract: This paper deals with the extraction of measurements for precision tracking of the centroid of a target from a forward looking infrared imaging sensor. The size of the target's image is assumed to be small, i.e., around 10 pixels. The statistical characterization of the centroid of a frame as a noisy linear measurement of the centroid of the target is obtained. Similarly, the statistical properties of the image correlation of two frames, which measures the target offset, are derived. Explicit expressions that map the video noise statistics into measurement noise statistics are obtained. The offset measurement noise is shown to be autocorrelated. Following this, state variable models for tracking the target centroid with these measurements are presented. Finally, simulations and quantitative conclusions about achievable subpixel tracking accuracy are given. It is shown that the filter that models the autocorrelated measurement noise provides the best performance.

Theory And Quantitative Comparison Of Doppler Centroid Estimation Methods

Abstract: ThE' Doppler centroid shift caused by the relative velocity between the sensor platform and the targets is derived by analysing the received SAR data. In contrast to the conventionally used AE-method (also called 'energy balancing'), which is a frequency approach, the two other methods, the Correlation Doppler Estimator (CDE) and the Sign Doppler Estimator (SDE), are both performed in the time domain.

Recognizing device for feature point position of work

Abstract: PURPOSE:To recognize a feature point within a window area with high accuracy by recognizing the position of an index point of a work which can be recognized with higher accuracy than the feature point of the work in an image and setting a window area based on said index point. CONSTITUTION:A hub H is picked up by an image input means 2 of a feature point position recognizing device 1 which recognizes the position and attitude through which the hub H is automatically attached to an automobile tire. The image of the hub H is stored in an image memory means 3. In this case, a mark hole M put on the tip of a hub bolt B protruded from the hub H is used as an index point and the image having an index point in the image stored in the means 3 is binarized by an image binarizing means 4. At the same time, the index point is specified and binarized based on the value of the tip part of the bolt B stored in a hab bolt threshold value setting means 5. A position recognizing means 6 calculates the centroid point of said index point. Then a window setting means 7 sets a window around the centroid point and a position recognizing means 10 recognizes the position and the attitude of the hub H.

Precision Target Tracking For Small Extended Objects

Abstract: We present a methodology for the tracking of the centroid of small extended objects using measurements from a forward looking infrared imaging sensor. The statistical characterization of the centroid of a frame as a noisy linear measurement of the centroid of the target is obtained. The off set measurement noise is shown to be autocorrelated. State variable models and the corresponding filters for tracking the target centroid with these measurements are presented. Their performances are compared and it is verified with simulations that the filter that models the autocorrelated measurement noise provides the best performance.

Picture processor for detecting real time center of gravity position

Abstract: PURPOSE:To detect the positions of center of gravity of plural objects with a video rate, by accumulating the coordinate and the number of image elements of a significant image element at every partial area for an input image, and calculating the centroid position from an added value at every label of the partial area. CONSTITUTION:The video signals of the objects 2 and 3 from a TV camera 1 are inputted to a processor via a synchronizing separator circuit 4 and a binarization circuit 5. And an S counter 7 counts the number of significant image elements of input binary information, and a Y counter 8 identifies a Y-axis coordinate at a prescribed point, and an X counter 9 identifies an X-axis coordinate, respectively, and each coordinate is added cumulatively at full adders 12 and 16, and respective count value is stored in a memory device 25 via a full adder 20. Based on the above stored value, a CPU 26 attaches the label which separates the partial area linked or non- linked mutually in the partial area where the area of the significant image element exceeds a prescribed value on the partial area, and calculates the centroid positions of the objects 2 and 3 at every set of a linked partial area by the label by using an accumulated coordinate value.

Movement simulation device for space robot

Abstract: PURPOSE: To enable simulation on the ground by providing a means deriving a differential equation to find the centroid position and posture angle of a space robot main body based on a total movement amount retention rule and angular momentum retention rule and an arithmetic means to calculate the centroid position and posture angle of the space robot by using a differential equation. CONSTITUTION: A differential equation to find the centroid position and attitude angle of a space robot main body 3 is derived based on a total movement retention rule and total angle movement amount retention rule by a differential equation deriving means 5. The time series of the centroid position and attitude angle of the space robot main body 3 are calculated by off-line or on-line by using the differential equation. Then, based on this time series data, the centroid position and attitude angle of the space robot main body 3 are interlocked with moving the arm of the space robot 2 and varied by a robot 1 for the ground. The simulation of the three dimensional space of the robot in an agravity space can be performed on the ground like this. COPYRIGHT: (C)1990,JPO&Japio

Morphological algorithms for centroid normalization in relational matching

Abstract: The effect of iterative morphological filters on the determination of centroids is examined. On sample binary images that are subjected to high-frequency variations on their boundaries, increasing iterative sequences of morphological openings and closings are observed to normalize the centroid position. When grosser (or more structured) distortions are introduced to the boundaries, the notion of a normalized centroid is less meaningful. In these cases, it is interesting to consider measurements on the charging centroid trajectory over the iterative filters as an alternative structural signature. In addition, morphological opening and closing distributions can serve as tools in structural matching. >

Motion analysis of a deformable object using subset correspondence

Abstract: A method is proposed to estimate generalized three-dimensional motion parameters for a deformable object using only subset correspondences between two successive time frames, eliminating a major preprocessing step. Only a small amount of information has to be processed, reducing the computation time significantly. The movement in three-dimensional space thus can be modeled by the deformation undergone by the object during the specified time instants, a rotation about a fixed axis passing through its centroid, and a translation. The goal is to estimate the generalized motion parameters (i.e. deformation, rotation, and translational components) with as little information (i.e. point/line correspondence) as possible from the data. >

Document display device

Abstract: PURPOSE:To make the contents of a document displayed on an opposite part to a moved end point unvariable by regarding an area based upon a centroid coordinates and area size as an area to be displayed after deformation and projecting the contents of a document on a part existing in the area to a deformed display area rectangular frame. CONSTITUTION:When the deformation of a display area is instructed by moving an optional end point in a rectangular frame, a difference between the centroid coordinates of the deformed display area and that of the undeformed display area is calculated, the centroid moving distance is converted into the centroid moving distance in the area to be displayed based on a coordinate conversion ratio and the centroid coordinates obtained by adding the converted centroid coordinates to the centroid coordinated in the undeformed displayed area is regarded as the centroid coordinates in the deformed displayed area. The vertical and horizontal sizes in the deformed display area are converted into the vertical and horizontal sizes in the displayed area based on the coordinate conversion ratio, an area determined by the centroid coordinates and the area size is regarded as the deformed displayed area and the contents of a document on a part existing in the area are deformed and then projected to the display area rectangular frame to redisplay the contents of the document. Consequently, the contents of the document displayed on the opposite part to the moved end point can be made unvariable.

Method for estimating posture of substance existing in three-dimensional space

Abstract: PURPOSE:To estimate the posture of a substance by sequencing the area ratios of respective faces of a model in the visual line axis direction in accordance with the relation of its centroid position, sequencing the area ratios of respective areas of a substance in accordance with the relation of its centroid position to obtain primary matching as a sequence and then obtaining secondary matching on the basis of areas converted into distances. CONSTITUTION:The model of an object is selected 1, the face vectors of plural faces and its centroid position vector are extracted 2, the image information of an object to be recognized is obtained 3 and divided 4 into ranges in accordance with density or the like, the area ratios of the ranges are rearranged 5 in a sequence corresponding to the centroid position, the components of respective face vectors are rearranged 6 in a sequence corresponding to the components of planes rectangular to the visual line axis of the centroid position vector, the visual line axis component ratios of respective faces are matched with the area ratios of respective ranges in accordance with the same sequence to execute primary matching 7, and the visual line axis components of respective faces expanded/contracted in accordance with distances up to a three-dimensional substance are similarly matched with the area of respective ranges to execute secondary matching.

A Doppler centroid estimation algorithm for SAR systems optimized for the quasi-homogeneous source

Abstract: Radar signal processing applications frequently require an estimate of the Doppler centroid of a received signal. The Doppler centroid estimate is required for synthetic aperture radar (SAR) processing. It is also required for some applications involving target motion estimation and antenna pointing direction estimation. In some cases, the Doppler centroid can be accurately estimated based on available information regarding the terrain topography, the relative motion between the sensor and the terrain, and the antenna pointing direction. Often, the accuracy of the Doppler centroid estimate can be improved by analyzing the characteristics of the received SAR signal. This kind of signal processing is also referred to as clutterlock processing. A Doppler centroid estimation (DCE) algorithm is described which contains a linear estimator optimized for the type of terrain surface that can be modeled by a quasi-homogeneous source (QHS). Information on the following topics is presented: (1) an introduction to the theory of Doppler centroid estimation; (2) analysis of the performance characteristics of previously reported DCE algorithms; (3) comparison of these analysis results with experimental results; (4) a description and performance analysis of a Doppler centroid estimator which is optimized for a QHS; and (5) comparison of the performance of the optimal QHS Doppler centroid estimator with that of previously reported methods.

Visual inspection device for pellet

Abstract: PURPOSE:To decide the appearance of a pellet regardless of the positional displacement and angular displacement of the pellet, and to eliminate the need for a reference pattern by measuring the peripheral section of the pellet and the barycentric coordinates of electrode sections from the regions of a white section and a black section in the inspection picture plane of the semiconductor pellet, measuring the distances of each barycentric coordinate and deciding the non-defective or defective appearance of the pellet. CONSTITUTION:The picture signal Si of a diode pellet Pi from a TV camera 1 is binary-coded by a binary-coding circuit 2 so that the peripheral section R of the pellet corresponds to a color such as black and an electrode E to a color such as white. The barycentric coordinates GR of a black section are measured by a centroid measuring circuit 4 in a binary-coded signal S2, and converted into the signal S2 as the black electrode E by an inversion appliance 3, and the barycentric coordinates GR are measured by a centroid measuring circuit 5. Both barycentric coordinates are read to a CPU 6, a distance between each barycentric coordinate is computed, and a defective decision output signal SO is output to a terminal 8 when the distance is kept within a predetermined range or more.

Improvement In Feature Interpretation By Means Of Polar Coding

Abstract: The paper presents improvement achievable in pattern recognition systems based on polar coding of images. The idea of polar coding of images is not a new one. Existing methods can be improved if, instead of radius and angle as the representatives of image boundary, other features are extracted, such as a histogram representing concentric luminous intensity of the image. The histogram is formed in such a way that it shows luminous intensity of concentric rings having center in template's centroid. The number of pixels per ring increases with growing radius and it is the greatest for outmost diameter. Therefore, integration of luminous information per ring must be normalized in order to form a histogram representation of polar image. Binary images are analyzed and generalization for gray scale images is given.

A recursive technique for adaptive vector quantization

Abstract: Vector Quantization (VQ) is fast becoming an accepted, if not preferred method for image compression. The VQ performs well when compressing all types of imagery including Video, Electro-Optical (EO), Infrared (IR), Synthetic Aperture Radar (SAR), Multi-Spectral (MS), and digital map data. The only requirement is to change the codebook to switch the compressor from one image sensor to another. There are several approaches for designing codebooks for a vector quantizer. Adaptive Vector Quantization is a procedure that simultaneously designs codebooks as the data is being encoded or quantized. This is done by computing the centroid as a recursive moving average where the centroids move after every vector is encoded. When computing the centroid of a fixed set of vectors the resultant centroid is identical to the previous centroid calculation. This method of centroid calculation can be easily combined with VQ encoding techniques. The defined quantizer changes after every encoded vector by recursively updating the centroid of minimum distance which is the selected by the encoder. Since the quantizer is changing definition or states after every encoded vector, the decoder must now receive updates to the codebook. This is done as side information by multiplexing bits into the compressed source data.

Reasoning About Camera Positioning Relative To Rectangular Patterns

Abstract: An algorithm to determine the three-space position and orientation of a robot camera relative to a rectangular shaped mark of known size has been developed. In contrast to similar research, this algorithm does not require that a priori constraints be placed on the original position or orientation of the camera relative to the mark. Given the image plane positions of at least three vertices of the mark, the two projected diagonals of the mark are isolated and processed in turn to find the 2d position of the camera in the plane that contains the diagonal and the line connecting the centroid of the mark and the focal point of the camera. The 2d results are then combined using heuristics to determine the unique three-space position and orientation of the camera relative to the rectangle. If fewer than three vertices are visible, camera repositioning parameters are computed such that relational determination can be achieved from a subsequent image. Results of camera position determination and an analysis of associated errors are provided.

Directivity discriminating device applying binary image processing

Abstract: PURPOSE:To identify the directivity even with an object having symmetrical property by defining the centroid of the object as a reference point and at the same time deciding a peculiar point viewed from the reference point as a deciding point for identification CONSTITUTION:The image of master parts is picked up by an image camera 41 and at the same time a signal Sy is binarized 31 The binarized signal Sb is written in a frame memory 32 While the signal Sb is read out by a CRT controller 37 and a master pattern is displayed on a display 42 A controller 37 sets the centroid and reference line of the master pattern Then a cursor is shifted on a display screen and a deciding point is set The deciding result (black/white information) of the deciding point is registered in a RAM 13 as master data The centroid and reference axis of the pattern of an object parts are obtained The black/white information on the cursor position is taken out and compared with the black/white information of the master pattern Based on this comparison information, the directivity of the subject pattern is outputted

Position recognizing method

Abstract: PURPOSE:To calculate the position and the angle of an object with high accuracy for an object assembling device by using an expanding/reducing function to detect the centroids of >=2 corner parts of the object together with >=2 corner parts remaining. CONSTITUTION:An object 1 irradiated by reflected or transmitted illumination is attached to a robot 7 serving as an assembling device. Otherwise subject 1 photographed by an image pickup device 3 set separately and the position and the angle of the object 1 are calculated by a video processor 5 with use of the video signals of the device 3. Then an expanding/reducing function is used to leave 2 corner parts of the subject 1 as they are and the position and the angle of the object 1 are calculated from the centroid coordinates of each corner part. Thus it is possible to eliminate the limitation for calculation of the angle done by the form of the object 1. Thus the position and the angle of the object 1 are calculated with high accuracy.

Laser transit anemometer software development program

Abstract: Algorithms were developed for the extraction of two components of mean velocity, standard deviation, and the associated correlation coefficient from laser transit anemometry (LTA) data ensembles The solution method is based on an assumed two-dimensional Gaussian probability density function (PDF) model of the flow field under investigation The procedure consists of transforming the data ensembles from the data acquisition domain (consisting of time and angle information) to the velocity space domain (consisting of velocity component information) The mean velocity results are obtained from the data ensemble centroid Through a least squares fitting of the transformed data to an ellipse representing the intersection of a plane with the PDF, the standard deviations and correlation coefficient are obtained A data set simulation method is presented to test the data reduction process Results of using the simulation system with a limited test matrix of input values is also given

Reference pattern registration system

Abstract: PURPOSE: To efficiently register a voice pattern by using a small number of memories by dividing the voice pattern into fixed states and registering the continuous time in every state and the centroid of a feature vector of a frame belonging to the state. CONSTITUTION: The system is provided with a microphone 1, a feature sequence conversion means 5, a voice pattern dividing means 3, a centroid calculating means 4, a continuous time calculating means 5, and a reference pattern registering part 6. A voice inputted from the microphone 1 is converted into the time sequence of feature vectors by the means 2. At the time, a voice pattern is divided into the fixed number N (N>1) of states and the continuous time of each state and the centroid of a feature vector of a frame belonging to the state are registered in each state. Consequently a quality reference pattern can be prepared by using the small number of memories.