Abstract
The products extruded from a granulating machine are easily smashed to powder by their physical characteristic, and their hydrous rate is changeable. So contact style quality analysis and batch analysis are difficult. Moreover, completely understanding quantitative relationship between many production factors and quality is never easy. On the other hand, production operator previously evaluated visually by knowledge based on his experience. So if a control system is considered, it seems to be effective to apply the computer vision methods on the quality estimation procedure. In this research, for the estimation, a texture is extracted from the product's surface, and each region of the product is recognized with extracting the contour using the steerable filter, simultaneously. And the classify to each quality is performed using a neuro-classifier, which learned from the teaching data of the operator's judgement on the quality.
