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Proceedings Paper

Classification techniques based on AI application to defect classification in cast aluminum
Author(s): Carlos Platero; Carlos Fernandez; Pascual Campoy; Rafael Aracil
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Paper Abstract

This paper describes the Artificial Intelligent techniques applied to the interpretation process of images from cast aluminum surface presenting different defects. The whole process includes on-line defect detection, feature extraction and defect classification. These topics are discussed in depth through the paper. Data preprocessing process, as well as segmentation and feature extraction are described. At this point, algorithms employed along with used descriptors are shown. Syntactic filter has been developed to modelate the information and to generate the input vector to the classification system. Classification of defects is achieved by means of rule-based systems, fuzzy models and neural nets. Different classification subsystems perform together for the resolution of a pattern recognition problem (hybrid systems). Firstly, syntactic methods are used to obtain the filter that reduces the dimension of the input vector to the classification process. Rule-based classification is achieved associating a grammar to each defect type; the knowledge-base will be formed by the information derived from the syntactic filter along with the inferred rules. The fuzzy classification sub-system uses production rules with fuzzy antecedent and their consequents are ownership rates to every defect type. Different architectures of neural nets have been implemented with different results, as shown along the paper. In the higher classification level, the information given by the heterogeneous systems as well as the history of the process is supplied to an Expert System in order to drive the casting process.

Paper Details

Date Published: 23 November 1994
PDF: 12 pages
Proc. SPIE 2249, Automated 3D and 2D Vision, (23 November 1994); doi: 10.1117/12.196088
Show Author Affiliations
Carlos Platero, Univ. Politecnica de Madrid (Spain)
Carlos Fernandez, Univ. Politecnica de Madrid (Spain)
Pascual Campoy, Univ. Politecnica de Madrid (Spain)
Rafael Aracil, Univ. Politecnica de Madrid (Spain)


Published in SPIE Proceedings Vol. 2249:
Automated 3D and 2D Vision
Rolf-Juergen Ahlers; Donald W. Braggins; Gary W. Kamerman, Editor(s)

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