Abstract
Edge detection is the keytechnique in image processing, image analysis, and image pattern recognition. In this paper, we propose the kind of adaptive edge detection algorithmbased on nonseparable sampling morphological wavelets. First we choose the sampling matrix according to the interesting edge direction;then decomposethe original image by nonseparable morphological wavelets to get the high frequency data with different directions; after that set the low frequency parts to zero; finallywe can get the edge of the original image by reconstruction. The algorithm has two advantages: one is adaptivefor edge detection because the parameters could be chosenaccording to the interesting edge direction; the other isto avoid the edge excursion since using small convolution kernel.
This work is supported by Hebei Science and Technology Key Support Program (Grant No.: 10243554D).
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Li, T., Guo, W. (2012). The Adaptive Edge Detection Algorithm Based on Nonseparable Sampling Morphological Wavelet. In: Zhang, Y. (eds) Future Wireless Networks and Information Systems. Lecture Notes in Electrical Engineering, vol 143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27323-0_33
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DOI: https://doi.org/10.1007/978-3-642-27323-0_33
Publisher Name: Springer, Berlin, Heidelberg
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