We describe here a system, based on boosting, for the classification of defects on material running on a production line. It is constituted of a two-stages architecture: in the first stage a set of features are extracted from the images surveyed by a linear camera located above the material. The second stage is devoted to the classification of the defects from the features. The novelty of the system resides in the ability to rank the defects with respect to a set of classes, achieving a rate of identification of dangerous defects very close to 100%.
Automatic classification of defects in an industrial environment / N.A. Borghese - In: New Directions in Neural Networks : 18th Italian Workshop on Neural Networks, WIRN 2008 / [a cura di] B. Apolloni, S. Bassis, M. Marinaro. - Amsterdam : IOS Press, 2009. - ISBN 9781586039844. - pp. 22-29 [10.3233/978-1-58603-984-4-22]
Automatic classification of defects in an industrial environment
N.A. BorghesePrimo
2009
Abstract
We describe here a system, based on boosting, for the classification of defects on material running on a production line. It is constituted of a two-stages architecture: in the first stage a set of features are extracted from the images surveyed by a linear camera located above the material. The second stage is devoted to the classification of the defects from the features. The novelty of the system resides in the ability to rank the defects with respect to a set of classes, achieving a rate of identification of dangerous defects very close to 100%.
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