Abstract
A new passive visual sensing system and special composed filter technology was developed firstly in this paper. Through the sensor, clearly welding gap image was collected. After regression recover, mean value smoothing, Laplace enhance, most noise was moved and gap edge became more evident. After analyzing the characters around welding gap, special straight line scanning was used. Then the gap edge was considered near the pixel gray value is the minimum on every scanning straight line. Extensively, because the gray value gradient of the gap edge is the local maximum, so the pixels on the two gap edges were found and were divided into two groups, at last, Hough transform was used to fit the two edges, and gap width and welding direction were calculated according to their definitions
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© 2007 Springer-Verlag Berlin Heidelberg
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Fan, C., Chen, S.B., Lin, T. (2007). Visual Sensing and Image Processing in Aluminum Alloy Welding. In: Tarn, TJ., Chen, SB., Zhou, C. (eds) Robotic Welding, Intelligence and Automation. Lecture Notes in Control and Information Sciences, vol 362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73374-4_32
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DOI: https://doi.org/10.1007/978-3-540-73374-4_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73373-7
Online ISBN: 978-3-540-73374-4
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