>The program is not available anymore and I do not have a copy.
>I believe it is used more for photo scanning of documents and books
>rather than real world images at a longer distance.
>
>However taking a straight on photo of a picket fence or equally spaced
>houses, should be able to produce a similar set of lines. Though one
>which an automatic coordinate extraction program would not be able to
>directly handle.
>
>But I understand how the program works in automatically finding the
>line crossings of the equally spaced parallel lines, and once it has
>determined those coordinates the rest is much like your spread sheet
>but with far more coordinates, spread over a larger radial range.
>
>That allows for better matching by least squares function fitting.
>Something IM already does for handing large numbers of 'control
>points' than the minimum needed for affine, perspective, or (still
>undocumented) polynomial distortions, in pixel coordinates.
>
>
>FYI  Polynomial Distortion
>   -distort polynomial  'order,  coordinate-pairs, ....'
>Where order is largest X or Y power of for the polynomial
>and determines the minimum number of coordinates needed
>   order    function       minimum coodinates
>     0       constant         1
>     1       affine           3
>    1.5      bilinear         4
>     2       quadratic        6
>     3       cubic           10
>     4       quartic         15
>     5       quintic         21
>
>For example a cubic distortion (order 3)
>distorts the image using the reverse mapping function
>    Xsrc =  a0 + a1*x + a2*y                        # affine terms
>         + a3*x*y                                   # bi-linear term
>         + a4*x^2 + a5*y^2                          # quadratic terms
>         + a6*x^3 + a7*x^2*y + a8*x*y^2 + a9*y^3    # cubic terms
>
>and a similar but completely separate Y coordinate mapping function.
>


Anthony,

Currently your least squares fit only works with X,Y coordinate to 
fit an X equation and a Y equation. I am not sure you have anything 
that will work directly with fitting a single polynomial in 
R=sqrt(X^2+Y^2). Or do you?


Fred
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