Automated Resistor Classification

In this group thesis, we develop an algorithm that allows the automated classification of resistors using image recognition. The algorithm is implemented in an Android app and therefore usable on every Android smartphone. The problem is split into parts and the result is obtained step by step beginning with the localization of the resistor in the captured image and cropping the image such that only the resistor’s body remains. In the following analysis, the color rings are separated from the background and finally assigned a specific color. In the end, it is possible to determine the resistance of the resistor. Our evaluation of the algorithm shows that the resistor localization works with nearly every image and also under different conditions. The detection of the color rings on the body of the resistor also performs well on most of the images. However, our approach to the color assignment turned out to be unreliable. The task is quite difficult because every camera has different saturation and brightness settings. Also, external conditions like shadows and the background have a significant impact on the colors in an image.