A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Custom-Built Moments for Edge Location
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometrical Multiscale Noise Resistant Method of Edge Detection
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Moments-Based Fast Wedgelet Transform
Journal of Mathematical Imaging and Vision
Sparse geometric image representations with bandelets
IEEE Transactions on Image Processing
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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(N2) for an image of size N ×N pixels. The experiments confirmed the effectiveness of the proposed method, also in the application to noisy images.