Abstract
This paper present a novel approach to edge detection in Gray-R grade rod barcode. The median filter keeps the image’s edge nonlinear characteristics well. So it was applied to the image filtering. Mathematical morphology was applied to the edge detection of Gray-R barcode image, with a smooth and clear extracted edge and a consecutive image skeleton. Maximum between-class variance method as its independence of the light intensity was used in the image segmentation. Probability statistics subdivision method was adopted in the accurate positioning of the image edge due to its simple algorithm and high implementation efficiency and precision. Measurement experiments show that these methods suppress the noise interference of the edge signal effectively, and improve the accuracy.
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Chen, G., Liu, J. (2012). Edge Detection Methods for Gray-R Barcode Grade Rod. In: Zhang, W. (eds) Software Engineering and Knowledge Engineering: Theory and Practice. Advances in Intelligent and Soft Computing, vol 162. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29455-6_41
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DOI: https://doi.org/10.1007/978-3-642-29455-6_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29454-9
Online ISBN: 978-3-642-29455-6
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