Using real time video feed to monitor analog gauge in Python

Question

I'm hoping someone here can help me go about trying to solve this problem. I'm trying to figure out a good way to use a real time video feed to run a python 0script when a pressure gauge that looks like this reaches a certain variable pressure.

I'm pretty confident that this shouldn't be too difficult as the gauge will be mounted in a fixed position in the image frame, but am new to this sort of stuff and really don't know where to start.

Any suggestions? Thanks in advance!

Answer 1

This problem could be much tougher than you think. Typically, people use OpenCV for image processing/pattern recognition problems. There are many excellent tutorials for Python available in the documentation

At it's core, your problem is the figure out the angle of rotation of the needle. Then from there, you can calculate what the pressure is. If you're lucky, you can find the needle using Feature Detection + Homography and then calculate the angle. But I have my doubts that this kind of image leads itself to feature detection.

Template Matching will be able to find the needle, but it's very sensitive to rotation, so you'd have to generate a large number of templates with different needle angles and then go through all of your templates every time you want a pressure reading.

It may well be faster, cheaper, and easier to use an electronic pressure gauge for reading pressure. There are any number of ways you can get the output of your electronic gauge into Python. Some gauges can be connected to the network. Some can communicate as a serial port with RS232/422 or USB.

If you can find a gauge with a digital display, it should be more straighforward to do some kind of OCR/Template Matching to read the display from a camera.

Edit:

@jeremy arsenault's comment prompted me to think of another solution. If you are focused mostly on detecting when the needle crosses a threshold, you could look for the leading edge of the dial. And you could look more towards the center of the dial, where there are no indicators.

This kind of image really lends itself to easy conversion to Thresholding to black and white. The dial is black and the background (at least towards the center) is white. After you do some Morphology and Thresholding of your image, you could look for black pixels of the dial. No template matching required. Pictures below illustrate some of the ideas. The first picture is your image thresholded to black and white. The starting image was very clean, but if you're grabbing from a camera, you'll probably have to do some Blurring, Morphology before thresholding to get no stray black pixels where you don't want them. The second image has a superimposed circle where you can look for black pixels. You can find the leading edge and trailing edge and average to get a fairly precise value of the center.

Some more implementation details/pseudocode. For computer images, origin is usually top left corner and +y goes down. Also, I've defined increasing angle theta with increasing pressure. Parametric equation for circle is

x = x0 - r*cos(theta + theta0)
y = y0 - r*sin(theta + theta0)

theta0 is the offset angle that gives zero pressure (around -45 degrees for gauge pictured. The brute force way to look for the needle would be to start sweeping the angle from zero and increasing until you find a black pixel at x,y. Then keep increasing until you find a white pixel at x,y. The average of the two angles gives you the center of the needle and you should be able to calculate pressure.