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Method and system for direct classification from three dimensional digital imaging

  • US 7,046,841 B1
  • Filed: 08/29/2003
  • Issued: 05/16/2006
  • Est. Priority Date: 08/29/2003
  • Status: Expired due to Fees
First Claim
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1. A method for processing digital image data taken from a three-dimensional topographic scene including terrain to extract discrete objects, the method comprising:

  • locating waypoints to define a centerline and a bounded area to be analyzed;

    defining the primary dimensional characteristics or attributes of the objects to be extracted from the image;

    defining finite element cells having a width dependent on the area of interest, a length dependent on the dimension of the objects and terrain variation and a height dependent on the discrete objects;

    mapping the finite element cells to a normalized coordinate base;

    grouping the digital image data, in the form of scanned three-dimensional point (x, y, z) coordinate points in Cartesian coordinate reference frames, into the finite element cells by determining eigenvalues and eigenvectors associated with each cell;

    classifying each of the three-dimensional points as simple local structures;

    composing globally complex structures from the local structures; and

    wherein spatial relationships of the three-dimensional coordinate points within each finite element cell are analyzed by calculating a 3×

    3 covariance matrix where Cj,k is the element in row j, column k in the matrix, (xi)j is the coordinate of point i in dimension j, n is the number of points in the cell, Nj is a normalization constant, Nk is a second normalization constant, mk is the mean value of the coordinates of the points in dimension k, and mj is the mean value of the coordinates of the points in dimension j, such that;

    C j , k = 1 n ·

    N j ·

    N k
    ·



    i


    [ ( x i ) j - m j ] ·

    [ ( x i ) k - m k ]
    calculating the eigenvalues and eigenvectors of the matrix, each eigenvector {right arrow over (e)}and corresponding eigenvalue λ

    satisfying the equation;




    {right arrow over (e)}=λ

    ·

    {right arrow over (e)}
    wherein C is a constant, and such that the three eigenvalues measure the spread of the data in the direction of the corresponding eigenvectors.

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