Detect marker in 2D image

I'm not directly in this field but I would tell you to start by looking into edge detection specifically. If you have a background in math/engineering the materials are pretty easy to understand:

This seemed to spark some ideas: http://www.cfar.umd.edu/~fer/cmsc426/lectures/edge1.ppt

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.

as always in computer vision, your first problem is image illumination and acquisition. before going further, establish how your markers will be printed on the ceiling, what their form will be, what light you will be using to see them, and what camera setup you will chose to look at the markers.

given a good material, a good light and a good camera, you may have no problem at all to process the image. for example, you can print a full arrow in a retro-reflective material, with a longer tail than your example, use a colored light and a corresponding filter on the camera. now all you have on your image is arrows... there are plenty other ways of acquiring the image that will help you there.

once you have plain arrows, a simple blob analysis (which consist of computing statistical moments of objects in the image) will give you a lot of informations: each arrow should have values almost equal for the 7 hu moments, which allows you to filter objects efficiently, also the orientation computed from the central moments will give you the angle of the arrow. blob analysis being only statistical, it is extremely fast.