Development of a Computerized Method to Inspect Empty Glass Bottle

Abstract

The objective of this study was to develop a computerized empty glass bottle inspection method in an attempt to replace manual inspection. The inspection system structure based on machine vision was illustrated in the article. Morphologic methods and wavelet transform were used to extract features of the bottle body and the finish from images. The fuzzy support vector machine neural network was adopted as the classifier when the features were extracted. The results of our experiment indicated that it can reach up to 97% of accuracy by using the method developed in this study to inspect empty glass bottles.