Page 17 - 中国仿真学会通讯2020第1期
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3. Extracting lines from the image based on the LSD                Then we extract and sort different values by
                                                             traversing the point set PFB. By slicing the point
    [17] algorithm                                           sets PFB along the Y⁃axis direction, we can get
                                                             the set of the left and right layers. Then we model
4. Removing the lines with a horizontal or vertical angle    it based on Algorithm 1 and Algorithm 2, thus we
                                                             can get the left and right layered model PLR and
greater than the threshold ki , leaving only the             the set of triangle patch TLR. The result is shown
                                                             in Figure 4 ( l ) . We extract and sort different z
approximate horizontal or vertical line. Here we let kl      values by traversing the point set PFB. By slicing
= 0.175                                                      the point sets PFB along the Z⁃axis direction, we
                                                             can get the set of the upper and lower layers. Then
5. Establishing the polar coordinate system and              we model it based on Algorithm 1 and Algorithm 2,
                                                             thus we can get the upper and lower layered model
    calculating the coordinates of each line based on        PUD and the set of triangle patch PUD. The result is
                                                             shown in Figure 4( n). Then, we merge the front
    equation ( 4 ) , the straight lines whose polar          and back layered model,the left and right layered
                                                             model and the upper and lower layered model. The
    coordinate difference satisfies the threshold, which     result is shown in Figure 4(o).
                                                             3.3  Roof Modeling Based on the Block
    is shown in equation(5) , are merged
                                                                    Reconstruction
             k      =  b  -  dc,( a  ≠ c,b  ≠ d)             We reconstruct the building roof based on the
                       a  -                                  block reconstruction method, which is shown as
                                                             the Algorithm 3. Algorithm 3 obtains a number of
                       ( )θ = arctan -  1                    quadrilateral sets by projecting the point cloud
                                        k                    onto a plane and using the color information of the
                                                             point cloud to block. For each quadrilateral, the
                    r = a·rcosθ + b·sinθ              (4)    geometric information of the point cloud is used
                                                             for reconstruction. The method of building the roof
    If a = c, it represents the vertical line. If b = d, it  model with the quadrilateral as the basic unit not
                                                             only can simplify the complexity of the model but
    represents the horizontal line. Where, ( a,b) and        also can facilitate texture mapping.

    ( c, d ) represent the coordinates of the two             Algorithm3 : Roof Modeling Based on the Block
                                                              Reconstruction
    endpoints of the line in the image coordinate
                                                              Input: The roof point cloud of the building
    system.
                                                              1. Projecting the roof point cloud onto the XOY plane,
                             dθ < Δθ                              and resampling and interpolating the projected point
                                                                  cloud into a picture ( Figure 4( p) ) .2. Detecting the
                             dr < Δr                  (5)         contour of the image based on Canny operator.

    Where,dθ is the angular difference between the two        3. Dividing the roof into blocks based on Hough⁃based
                                                                  line extraction method ( Figure 4( q) ) .
    lines, dr is the radius difference between the two
                                                              4. Reconstructing the 3D model of the roof based on the
    lines. Δθ and Δr are the thresholds of the angular            method of block reconstruction ( Figure 4( r) ) .

    difference and the radius difference. This method

    takes Δr = 5,Δθ = 10 °

6. Dividing the lines into a group of horizontal lines and

a group of vertical lines based on ( r, θ ) , and

segmenting the image into ( m+ 1) ×( n+ 1) blocks,

where m,n represent the number of horizontal lines

and vertical lines

7. Traversing all blocks and counting the number of

    black pixel and white pixel in each block.

    if the number of white pixel > the threshold kw

      and the number of white pixel is much larger than

    the number of black pixel

        Marking the block as an effective block

        Adding the four vertices to the set of output

    model points PFB

    else

        continue

8. Triangulating the point set PFB , and obtaining the

    triangular patch TFB of the model of the front and

    back layers. The result is shown in Figure 4( j)

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