Abstract
Classical Canny Operator plays an important role in the image edge detection. The paper analyses the theory of the traditional Canny edge algorithm and does some improvements on the parts of smoothing filter selection, point amplitude calculation, and high or low threshold selection. The improved Canny algorithm uses B-spline function instead of Gaussian function; calculates gradient amplitude in 3×3 neighborhoods; and selects thresholds on the basis of gradient histogram. The experiment proves that the new algorithm improves the accuracy of positioning and provides a better and evident de-noising effect.
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© 2011 Springer-Verlag Berlin Heidelberg
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Li, J., Ding, S. (2011). A Research on Improved Canny Edge Detection Algorithm. In: Zhang, J. (eds) Applied Informatics and Communication. ICAIC 2011. Communications in Computer and Information Science, vol 228. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23223-7_13
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DOI: https://doi.org/10.1007/978-3-642-23223-7_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23222-0
Online ISBN: 978-3-642-23223-7
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