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Asked: 2026-05-12T21:34:58+00:00

I am hoping to obtain some some help with 2D object detection. I’ll give

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I am hoping to obtain some some help with 2D object detection. I’ll give a brief overview of the context in which this will be implemented.

There will be an image taken of the ceiling. The ceiling will have markers placed on it so the orientation of the camera can be determined. The pictures will always be taken facing straight up. My goal is to detect one of these markers in the image and determine its rotation. So rotation and scaling(to a lesser extent) will be the two primary factors used in the image detection. I will be writing the software in either C# or matlab(not quite sure yet).

For example, the marker might be an arrow like this:

Reference Arrow

An image taken of the ceiling would contain markers. The software needs to detect a single marker and determine that it has been rotated by 170 degrees.

Ceiling Arrows

I have no prior experience with image analysis. I know image processing is a fairly broad topic and was hoping to get some advice on which direction I should take and which techniques would be best for my application. Thanks!

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1 Answer

  1. Editorial Team

    I’d recommend MATLAB or if you’re intent on using C#, Emgu CV is pretty good.

    Hough transforms are a great idea. Once you detect the edges in your image, using, say a Canny edge detector, you get an edge image (which is binary image with only 1 or 0 for values).

    Then, the Hough straight line transform (essentially) spins a line about each white pixel in the edge image (the resolution of the line depends on you) using a parametrized function for the line and calculates the total number of white (valued at 1) pixels along each spun line and stores this information in a big accumulator which stores the data indexed by the parameters of the line.

    alt text http://upload.wikimedia.org/wikipedia/en/a/af/Hough_space_plot_example.png

    In the example above, the parametric form for a line is:

    rho = x*cos(theta) + y*sin(theta)

    where rho is the distance and theta is
    the angle

    So as you can see the, if you look at the bin at a particular orientation you can find out how many lines are oriented at that angle. Of course, you’ll have to do some extra work to figure out which lines are oriented at that angle since you have 5 other lines per arrow but that shouldn’t be too hard.

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