Authors:
Ryosuke Suzuki
1
;
Fumihiko Sakaue
1
;
Jun Sato
1
;
Ryuichi Fukuta
2
;
Taketo Harada
3
and
Kazuhisa Ishimaru
4
Affiliations:
1
Nagoya Institute of Technology, Gokiso Showa, Nagoya, Japan
;
2
DENSO Electronics Corporation, 1-21 Miyama, Shinpukujicho, Okazaki, Japan
;
3
DENSO Corporation, 1-1, Showa-cho, Kariya, Japan
;
4
SOKEN Inc., 1-1, Showa-cho, Kariya, Japan
Keyword(s):
Multispectral BTF, Bidirectional Texture Function, Bidirectional Reflectance Distribution Function, One-class Classifier.
Abstract:
In this paper, we propose a method to inspect coatings of industrial products in a factory automation system. The coating of industrial products is important because the coating directly affects the impression of the product, and a large amount of cost is spent on its inspection. Because lots of colors are used in the coating of industrial products, as well as there are various surface treatments such as matte and mirror finishes, the appearance of these products varies hugely. Therefore, it is difficult to obtain the properties of the surfaces by ordinary camera systems, and thus, they are inspected manually in the current system in most cases. In this paper, we present a method of representing surface properties of them, called multispectral BTF, by taking products under narrow-band light from various directions. We also show a method for inspection using a one-class discriminator based on Deep Neural Network using the multispectral BTF. Several experimental results show that our p
roposed BTF and one-class classifier can inspect various kinds of coating.
(More)