MCBP Neural Network for Efficient Recognition of Tire Classification Code


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 4, No. 2, pp. 465-482, Feb. 1997
10.3745/KIPSTE.1997.4.2.465,   PDF Download:

Abstract

In this paper, we have studied on constructing code-recognition system by neural network according to a image process taking the DOT classification code stamped on tire surface. It happened to a few problems that characters distorted in edge by diffused reflection and two adjacent characters take the same label, even very sensitive to illumination for recognition the stamped them on tire. Thus, this paper would propose the algorithm for tire code under being conscious of these properties and prove the algorithm efficiency with a simulation. Also, we have suggested the MCBP network composing of multi-linked recognizers for efficient identify the DOT code being tire classification code. The MCBP network extracts the profection value for classifying each character's region after taking out the projection of each character''s region on X, Y axis, processes each characters by taking 7X8 normalization.


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Cite this article
[IEEE Style]
K. G. Seo and O. H. Seok, "MCBP Neural Network for Efficient Recognition of Tire Classification Code," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 4, no. 2, pp. 465-482, 1997. DOI: 10.3745/KIPSTE.1997.4.2.465.

[ACM Style]
Koo Gun Seo and Oh Hae Seok. 1997. MCBP Neural Network for Efficient Recognition of Tire Classification Code. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 4, 2, (1997), 465-482. DOI: 10.3745/KIPSTE.1997.4.2.465.