Defect Classification on Automobile Tire Inner Surfaces with Functional Classifiers

Author:

Tada Hirotaro1,Sugiura Akihiko2

Affiliation:

1. The Yokohama Rubber Co., Ltd.

2. Graduate School of Science and Technology, Shizuoka University

Publisher

The Institute of Systems, Control and Information Engineers

Reference16 articles.

1. [1] T. Funatomi, M. Iiyama, K. Kakusho and M. Minoh: Light stripe triangulation for multiple moving objects; The IEICE Transactions on Information and Systems, Vol. J90-D, No. 8, pp. 1858–1867 (2007) (in Japanese)

2. [2] E. Takahashi, N. Sakoda, T. Morimoto, T. Nonaka, S.Horiguchi and Y. Matsushita: Three dimensional profile measurement system for tire surface using ultra high speed image processing camera; R&D Kobe Steel Engineering Reports, Vol. 58, No. 2, pp. 62–66 (2008) (in Japanese)

3. [3] E. Takahashi, K. Araki, N. Sakoda, H. Takeda, M. Murakami and Y. Matsubara: Tire surface-profile inspection system using information of “Tire KANAGATA (die) Design”; Transactions of Society of Automotive Engineers of Japan, Vol. 46, No. 1, pp. 213–218 (2015) (in Japanese)

4. [4] T. Funahashi, T. Fujiwara, A. Kaneko and H. Koshimizu: Tire visual inspection of exterior thin defects—Defects feature measurement by using light stripe method enforced with rotation eccentricities suppression—; Journal of the Japan Society for Precision Engineering, Vol. 80, No. 12, pp. 1200–1205 (2014) (in Japanese)

5. [5] Y. LeCun, L. Bottou, Y. Bengio and P. Haffner: Gradient-based learning applied to document recognition; Proceedings of the IEEE, Vol. 86, No. 11, pp. 2278–2324 (1998)

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