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Proceedings Paper

Conceptual framework design for integrated visual inspection system
Author(s): Yasuhiro Ueda; Shuhei Yamamoto; Tamon Iden; Masakazu Yanase; Yoshihide Shigeyama; Atsuyoshi Nakamura
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Paper Abstract

This paper describes a framework for automatic generation of an image processing algorithm that consists of preprocessing, feature extraction, classification and algorithm evaluation modules based on machine learning. With a view to applying the generated algorithm to industrial visual inspection system, we intend to offer a framework model equipped with the below-mentioned features. Also, we want to report on the experimental result of the offered model. 1.Automatically generate by machine learning an image processing algorithm to extract regions that have same characteristics as specified by users. 2.Generate in particular a high-precision image processing algorithm, improving the level of statistical separation between true and false defects that may cause a deterioration factor in classification accuracy. 3.Optimize an image improving filter sequence in preprocessing modules by means of GA (Genetic Algorithm).

Paper Details

Date Published: 25 October 2004
PDF: 10 pages
Proc. SPIE 5603, Machine Vision and its Optomechatronic Applications, (25 October 2004); doi: 10.1117/12.580587
Show Author Affiliations
Yasuhiro Ueda, Sharp Corp. (Japan)
Shuhei Yamamoto, Sharp Corp. (Japan)
Tamon Iden, Sharp Corp. (Japan)
Masakazu Yanase, Sharp Corp. (Japan)
Yoshihide Shigeyama, Sharp Corp. (Japan)
Atsuyoshi Nakamura, Sharp Corp. (Japan)

Published in SPIE Proceedings Vol. 5603:
Machine Vision and its Optomechatronic Applications
Shun'ichi Kaneko; Hyungsuck Cho; George K. Knopf; Rainer Tutsch, Editor(s)

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