Neural networks inspection system for glass bottles production: a comparative study

摘要

This paper describes a vision system that detects cracks in glass bottles production. The first step consists in collecting prototypes of bottles with and without defects. A Sequence of 16 images is captured by a matrix camera while each bottle rotates in Front of a specific lighting system. The second step is concerned with morphometric And photometric features extraction. The subsequent decision step is performed by Different neural networks, such as MLP, RBF, PNN and LVQ.