Abstract
In this study, the Knowledge Discovery Database (KDD) was used to aid the computer to visualize, recognize and classify workpieces automatically through intelligent identification. In order to acquire initial statistical shape features, smooth and segment workpieces images were accurately taken and the shape features were stored into a database. Rough Set and Relevancy Analysis was used to reduce the shape features in order to generate the minimum characteristic vector. Finally, the generated classification rules were used to guide semantic recognition as prior knowledge. The algorithm is verified on four different types of workpieces, and the results showed that the obtained shape features are suitable for object classification and recognition semantically. This paper provides a new technique of image processing of machine vision and has great significance in the future study.
Published Version
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