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JRM Vol.5 No.1 pp. 73-78
doi: 10.20965/jrm.1993.p0073
(1993)

Paper:

A Method for Measuring Depth Using Fuzzy Reasoning and a Modified Implicit Function

Kazuo Yamaha, Hiroshi Tominaga*, Tatsuya Nakamura** and Yoichi Miyake***

Mechanical Engineering Laboratory, AIST,
1-2 Namiki, Tsukuba, lbaraki 305, Japan

*Ibaraki Prefectural Industrial Engineering Center,
3871-1, Ibaraki-cho, Higashi-Ibaraki-gun, Ibaraki 31 1-31, Japan

**Department of Mechanical Engineering, Mie University,
Kamihama 1515, Tsu, Mie 514, Japan

***Faculty of Engineering, Chiba University,
1-33, Yayoi-cho, Inage-ku, Chiba 260, Japan

Received:
December 12, 1992
Accepted:
January 7, 1993
Published:
February 20, 1993
Keywords:
Fuzzy set theory, Digital image processing, Mechatronics, Depth Measurement method, Robot vision, Monocular vision, Blurred image, Modified implicit function
Abstract

Many scientists and engineers are interested in three-dimensional (3-D) vision for robots. The focus of this paper is to describe a newly developed measuring technique for 3-D robot vision which employs a blurred image method to obtain depth perception. The measuring system consists of only one camera and an image processor. Several basic experiments were done using a checkered 3-D object and a new type of modified fuzzy reasoning. A new membership function is defined from two kinds of equations using a modified implicit function. As a result, the relationship between the measured distance and the estimated distance was found to be linear. This blurred image method together with fuzzy reasoning was found to be very effective in depth measurement of 3-D objects.

Cite this article as:
K. Yamaha, H. Tominaga, T. Nakamura, and Y. Miyake, “A Method for Measuring Depth Using Fuzzy Reasoning and a Modified Implicit Function,” J. Robot. Mechatron., Vol.5, No.1, pp. 73-78, 1993.
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Last updated on Jul. 12, 2019