Edge detection by multiscale merging

Presents multiscale edge detection on real world images. These images are often 3D and the lens field depths used cause a blur of the edges to be detected. The work is based on a generalization of the Canny-Deriche filter, modeled by a more realistic edge than the traditional ramp form edge. This filter can be used to generate a frame of wavelet. For the merging of the decomposition data, the authors use a geometrical classifier developed in their laboratory. The segmentation system thus set up and after the training phase does not require any adjustment nor parameter.<
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