This week I explored computer vision algorithms to separate the components from the rest of the circuit. In order to properly do this, I came up with the idea to have circular nodes at the end of every component’s two terminals. Then, I will use an algorithm to detect circles such as the Hough Circle’s algorithm in order to find these nodes. Next, each node that is found will have an algorithm run upon it in which it will find the closest nodes in the same x and y coordinates. Then, a bounding box will be drawn between the sets of two dots and this box will be looked at to find a component.
I tried to implement this with a simple picture of a resistor but was unable to get it to work. The circles were not being detected in the image. I tried to run a simple filter on the image to detect the components being drawn. I made every pixel that had a black value of over a threshold value completely black, and every pixel with a lower black value completely white. This also did not work well in differing light conditions like the picture below.
Furthermore, the circles on the end of the resistor were not even detected. I believe I need to look further into the problem because we need to make sure we can detect components separately from the whole circuit. I tried a contour plot which detected edges relatively well, but the nodes on each component were not filled in because the contour plot only detects edges. This is problematic because we will have other circular components like voltage and current sources that we will need to ensure By individually identifying components and wires with this technique, we can easily build a netlist for our circuit simulator. I also briefly explored the concept of netlists and how they work so that we can implement it for our circuit simulator.
I am still on track with the schedule because I am still researching CV algorithms. I want to have a picture of a resistor with the circles on its ends being detected properly by our circle detection algorithm. This will prove that we can go on with the technique I discussed above to detect individual components.