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  • [Matlab] Walking along a path

    Last month I was experimenting with an algorithm in which I needed to construct a set of equidistant steps along a path consisting of line segments. (I'll call this a polyline path, or polyline for short.) Today I want to show you how to construct such a path in MATLAB. Along the way I'll show you the function improfile and give you a pointer to a database of sample range images that I found.

    Contents

    Polylines

    Here's a simple example of a polyline. (Note that, because we're going to be talking about distances, I'm going to set the aspect ratio of my plots to be 1:1 by calling axis equal.)

    x = [24 214 327 617];
    y = [375 223 218 341];
    plot(x,y)
    axis equal
    
    polyline_path_01

    This has three connected line segments. In this example, each segment has a different length. I wanted to be able to find a certain number of points that were equally spaced along this path.

    IMPROFILE

    After pondering this problem for a minute or so, I remembered that the function improfile does exactly this computation internally. The function improfile is used to compute pixel-value profiles along a user-specified polyline.

    Let me illustrate improfile using a range image. In a range image, the pixel values represent estimated distance from the imaging device. I found the USF (University of South Florida) Range Image Database online. Below is a range image I downloaded from the database. It was taken by the Vision Lab at USF using a "K2T structured light camera." (No, I don't know what that is.) The web site helpfully tells me that the image is stored in "rasterfile format," which is pretty dated but fortunately supported by imread.

    url = 'http://blogs.mathworks.com/images/steve/2012/chessmen.range';
    I = imread(url, 'ras');
    imshow(I, 'InitialMagnification', 50)
    
    polyline_path_02

    Let's use improfile to compute a cross-section of range values along a particular path. First, though, let me superimpose the path on the image so you can where it is. (Although improfile has an interactive mode that lets you select the path using a mouse, I can't show that here.)

    hold on
    plot(x,y,'r','LineWidth',5)
    hold off
    
    polyline_path_03

    Here's the cross-section of range values.

    improfile(I,x,y)
    
    polyline_path_04

    You can see that improfile shows the cross-section as a 3-D plot. To see the cross-section as a normal 2-D line plot, call improfile with an output argument to get the cross-section values and then pass them to plot.

    c = improfile(I,x,y);
    plot(c)
    
    polyline_path_05

    Computing equidistant steps along the polyline

    As part of its computation, improfile needs to compute equidistant steps along the polyline path. So how does that work?

    The function first computes the cumulative distance from the beginning of the polyline to each vertex along the way, and then it uses a clever call to interp1 to compute the steps.

    xy = [x' y'];
    d = diff(xy,1)
    
    d =
    
       190  -152
       113    -5
       290   123
    
    
    dist_from_vertex_to_vertex = hypot(d(:,1), d(:,2))
    
    dist_from_vertex_to_vertex =
    
      243.3187
      113.1106
      315.0063
    
    
    cumulative_dist_along_path = [0;
        cumsum(dist_from_vertex_to_vertex,1)]
    
    cumulative_dist_along_path =
    
             0
      243.3187
      356.4293
      671.4356
    
    

    Now we can get our steps by constructing a call to interp1.

    num_points = 20;
    dist_steps = linspace(0, cumulative_dist_along_path(end), num_points);
    points = interp1(cumulative_dist_along_path, xy, dist_steps)
    
    points =
    
       24.0000  375.0000
       51.5949  352.9241
       79.1898  330.8482
      106.7847  308.7722
      134.3796  286.6963
      161.9745  264.6204
      189.5694  242.5445
      218.0483  222.8209
      253.3525  221.2587
      288.6567  219.6966
      323.9609  218.1345
      356.7328  230.6108
      389.2662  244.4095
      421.7996  258.2081
      454.3330  272.0068
      486.8664  285.8054
      519.3998  299.6041
      551.9332  313.4027
      584.4666  327.2014
      617.0000  341.0000
    
    

    Plot the points, superimposing them on the original path, to see how we did.

    plot(x,y)
    hold on
    plot(points(:,1), points(:,2), 'o')
    hold off
    axis equal
    
    polyline_path_06

    There you go. Now you know about improfile, you know how to compute a path along a polyline, and you know about an online database of sample range imagery.

    I think we should call it a day.

    From: Steve on Image Processing

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  • 原文地址:https://www.cnblogs.com/youth0826/p/2589904.html
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