Abstract
In this paper the sliding wedgelet algorithm is presented together with its application to edge detection. The proposed method combines two theories: image filtering and geometrical edge detection. The algorithm works in the way that an image is filtered by a sliding window of different scales. Within the window the wedgelet is computed by the use of the fast moments-based method. Depending on the difference between two wedgelet parameters the edge is drawn. In effect, edges are detected geometrically and multiscale. The computational complexity of the sliding wedgelet algorithm is O(N 2) for an image of size N ×N pixels. The experiments confirmed the effectiveness of the proposed method, also in the application to noisy images.
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Lisowska, A. (2011). Edge Detection by Sliding Wedgelets. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21593-3_6
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DOI: https://doi.org/10.1007/978-3-642-21593-3_6
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