This paper aims to inspect solder joint defects of integrated circuit (IC) components on printed circuit boards. Here, an IC solder joint inspection algorithm is developed based on a Gaussian mixture model (GMM).
First, the authors train a GMM using numerous qualified IC solder joints. Then, the authors compare the IC solder joint images with the trained model to inspect the potential defects. Finally, the authors introduce a frequency map and define a metric termed as normalized defect degree to evaluate qualities of the tested IC solder joints.
Experimental results indicate that the proposed method is superior to the state-of-the-art methods on IC solder joint inspection.
The approach is a promising method for IC solder joint inspection, which is quite different from the traditional classifier-based methods.
