Abstract
Various derivatives (1st to 4th order) describe different signal characters in scale space: the first derivative represents signal variation which can be used for coding; the second derivative characterizes the size of signal local structure and can be used for adaptive smoothing; the third and fourth order derivatives relate zero-crossing(or other features) contour in scale space to a differential equation which can be used for feature tracking and make quantitative measurements of zero-crossing properties possible. In the case that different derivatives are calculated by a special class of derivative filters, all the derivative signals can be treated in the same way.
This work is supported by the Chinese National Natural Science Foundation and Sino-France Co-operation Project
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© 1996 Springer-Verlag Berlin Heidelberg
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Cong, G., Ma, S. (1996). Derivatives in scale space. In: Perner, P., Wang, P., Rosenfeld, A. (eds) Advances in Structural and Syntactical Pattern Recognition. SSPR 1996. Lecture Notes in Computer Science, vol 1121. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61577-6_8
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DOI: https://doi.org/10.1007/3-540-61577-6_8
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