During our demo this week, I presented the work I’ve done for the CV / OCR aspects of our project. I’ve managed to get the character location recognition accuracy very high with a reasonably good image. Letter recognition seems to be around 80-85 % but I plan to add characters to the nearest-neighbor database to hopefully increase this. Additionally, I will implement the necessary logic to capture images and process when necessary. Furthermore, I will help with the other work (integration, final presentation, poster, etc) as we enter the final weeks.
“what new tools or new knowledge did you find it necessary to learn to be able to accomplish these tasks? What learning strategies did you use to acquire this new knowledge?”
Computer vision was very new to me, and I was able to familiarize myself with key components of preprocessing, optical character recognition, and even the implementation of a simple nearest-neighbor classification model. This also introduced a somewhat new style of testing, as most of the testing necessary involved manually observing the output of preprocessing stages. Primary learning strategies included reading articles and publications on CV / OCR, looking through code examples similar to what I was trying to accomplish, and simply working hands-on with the techniques.