Stephen R. Niezgoda1, Surya R. Kalidindi1,2
CMC-Computers, Materials & Continua, Vol.14, No.2, pp. 79-98, 2009, DOI:10.3970/cmc.2009.014.079
Abstract The generalized Hough transform is a common technique for feature detection in image processing. In this paper, we develop a size invariant Hough framework for the detection of arbitrary shapes in three dimensional digital microstructure datasets. The Hough transform is efficiently implemented via kernel convolution with complex Hough filters, where shape is captured in the magnitude of the filter and scale in the complex phase. In this paper, we further generalize the concept of a Hough filter by encoding other parameters of interest (e.g. orientation of plate or fiber constituents) in the complex phase, broadening More >
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