A maker shared an electronics project on Digikey that explains an automatic system for recognizing and organizing resistors using an Arduino Uno Q. Zach Hipps did the work and looked for methods to cut down the time needed to manually figure out resistor values after making electronics prototypes. The project uses computer vision methods instead of manually reading color codes.
The system starts with a USB camera, which is later switched out for a USB microscope, both linked to the Arduino Uno Q that operates within a Linux setup. Instead of using a machine learning model, the system detects resistor color bands by first preparing the image through preprocessing, converting it to a different color space, and then analyzing the shapes using contour detection. The software figures out the resistor values correctly by looking at the sequence and colors of the detected bands.
Testing confirmed that the system accurately recognized various resistor values, such as typical ones and those with higher resistance. The project shows how the Arduino Uno Q, which includes both a microcontroller and a microprocessor, can be used to perform real-world computer vision applications. The author suggests that these same methods might also be used for solving other issues related to organizing workshops, like arranging hardware parts.
A Maker Demonstrates Automated Resistor Sorting Using Arduino Uno Q and Computer Vision
