Title :
Three-dimensional feature detection using optimal steerable filters
Author :
Aguet, François ; Jacob, Mathews ; Unser, Michael
Author_Institution :
Biomedical Imaging Group, Ecole Polytech. Fed. de Lausanne, Switzerland
Abstract :
We present a framework for feature detection in 3-D using steerable filters. These filters can be designed to optimally respond to a particular type of feature by maximizing several Canny-like criteria. The detection process involves the analytical computation of the orientation and corresponding response of the template. A post-processing step consisting of the suppression of non-maximal values followed by thresholding to eliminate insignificant features concludes the detection procedure. We illustrate the approach with the design of feature templates for the detection of surfaces and curves, and demonstrate their efficiency with practical applications.
Keywords :
feature extraction; filtering theory; Canny-like criteria; nonmaximal values suppression; optimal steerable filters; three-dimensional feature detection; Biomedical imaging; Computer vision; Convolution; Detectors; Eigenvalues and eigenfunctions; Filtering; Isosurfaces; Jacobian matrices; Nonlinear filters; Polynomials;
Conference_Titel :
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN :
0-7803-9134-9
DOI :
10.1109/ICIP.2005.1530266
