Fortunately, one of the examples in the OpenCV Python set is a program named edge.py. The following is that file (with blank lines removed):

This program uses the Canny image detection algorithm implemented by OpenCV to find the edges in any image. For more on the Canny edge algorithm, refer to http://dasl.mem.drexel.edu/alumni/bGreen/www.pages.drexel.edu/_weg22/can_tut.html or http://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_imgproc/py_canny/py_canny.html. You captured an image earlier; you can use this program to look at the edges and to also see how setting a different threshold can show more/less edges. Run the program with the image captured earlier and you will see the following:

You will notice that there is a threshold slide bar setting at the top. If you adjust this threshold up, it will find fewer edges—the edges that have a larger threshold. The picture for a setting of 30 is as follows:

Now you can see how this process could be translated to an image of a blank floor and a barrier. The following is such an image with a possible barrier:

You can calibrate the distance to the object based on the pixels and the position of the camera.