A Neuro-Symbolic Hybrid System Methodology for Quality Inspection on Artificial Textures

The Neuro-Symbolic Hybrid Systems (NSHS) are used to solve problems where there exists a necessity of combining and integrating the artificial neural networks and the symbolic representations in only one system in order to obtain better results. We developed a NSHS Methodology to integrate the knowledge of a human expert and the numeric knowledge obtained from a computer vision process. We implement the methodology to solve a quality inspection problem in artificial textures. The construction of neuro-symbolic integration strategies allows us defining an adequate type of neuro-symbolic system to obtain an increment of the efficiency of an inspection task, which is shown with the better results obtained compared with other approaches. Key-Words: Computer Vision, Neuro-Symbolic Hybrid Systems, Artificial Neural Networks, Production Rules