We began making more progress on our pin classification using both deep learning and feature extraction. These two approaches are being experimented with and in the next two weeks we will choose one to develop for rest of the semester.

For the feature extraction method, we initially colored the central ring of the plug. This bright color of green allowed us to match pixels by color in order to reliably find the ring in software. From there, an ellipsis is matched to the ring to find our boundary for pin identification. Additional dots were made that identify the center and top of ring.

The deep learning approach has been implemented as a branch of our original plug classifier. We need to perform further testing and tuning on this part. Initial results show that the model may have difficult classifying fine-grain differences between pins.

We are excited to present for QRB 1 next week and hear feedback about our approaches.