NDLI: Inspection of Visible and Invisible Features of Objects with Image and Sound Signal Processing

Content Provider	IEEE Xplore Digital Library
Author	Yamashita, A. Hara, T. Kaneko, T.
Copyright Year	2006
Description	Author affiliation: Dept. of Mechanical Eng., Shizuoka Univ. (Yamashita, A.; Hara, T.; Kaneko, T.)
Abstract	In this paper, we propose a new method that can inspect visual and non-visual features of objects simultaneously by using image and sound signal processing techniques. A method for discriminating a property of an object with the use of generated sound when striking it with a hammer is called a hammering test. This method can investigate non-visual features of objects such as inner structure of objects, e.g., the existence of defects and cracks inside objects. However, this method depends on human experience and skills. In addition, if we perform this test over a wide area of objects, it is required to manually record hammering positions one by one. To solve these problems, this paper proposes a hammering test system consisting of two video cameras that can acquire image and sound signals of a hammering scene. The shape of the object (visual feature) is measured by the image signal processing from the result of 3-D measurement of each hammering position, and the thickness or material (non-visual feature) is estimated by the sound signal processing in time and frequency domains. The validity of proposed method is shown through experiments
Starting Page	3837
Ending Page	3842
File Size	604682
Page Count	6
File Format	PDF
ISBN	1424402581
DOI	10.1109/IROS.2006.281790
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Inspection Acoustic signal processing Shape measurement Acoustic testing Frequency measurement Position measurement Thickness measurement Time measurement Video signal processing Humans
Content Type	Text
Resource Type	Article

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