IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection of Artificial Structures in Natural-Scene Images Using Dynamic Trees
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Wedgelet Enhanced Appearance Models
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 12 - Volume 12
Custom-Built Moments for Edge Location
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIAM Journal on Scientific Computing
Geometrical Multiscale Noise Resistant Method of Edge Detection
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Image analysis by Tchebichef moments
IEEE Transactions on Image Processing
Sparse geometric image representations with bandelets
IEEE Transactions on Image Processing
Edge detection by sliding wedgelets
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
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In the paper the moments-based fast wedgelet transform has been presented. In order to perform the classical wedgelet transform one searches the whole wedgelets' dictionary to find the best matching. Whereas in the proposed method the parameters of wedgelet are computed directly from an image basing on moments computation. Such parameters describe wedgelet reflecting the edge present in the image. However, such wedgelet is not necessarily the best one in the meaning of Mean Square Error. So, to overcome that drawback, the method which improves the matching result has also been proposed. It works in the way that the better matching one needs to obtain the longer time it takes. The proposed transform works in linear time with respect to the number of pixels of the full quadtree decomposition of an image. More precisely, for an image of size N脳N pixels the time complexity of the proposed wedgelet transform is O(N 2log驴2 N).