Code covered by the BSD License
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cedge(E, ln)
% Clears the unimportant edges on the binary image based on the edge
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click(I, varargin)
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gfht(src, patt, rhorange, the...
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htcircles(im, minR, maxR, max...
% HTCIRCLES detects multiple disks in a binary image using Hough Transform.
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iminvert(I)
% IMINVERT inverts the grayscaled input image in the range [0 255]
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imnorm(I, dr)
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ndiff(A)
% Accounts for the number of different elements that compose the matrix A
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pcircle(center, radius, varar...
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pcircles(fhdl, center, radius...
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pline(p1, p2, varargin)
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rdirproc(wdir, varargin)
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gfht_demo1.m
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gfht_demo2.m
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View all files
generalized fuzzy Hough transform
by Pau Micó
07 Oct 2010
Fuzzy version of the generalized Hough transform
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| File Information |
| Description |
Noisy environments make difficult the pattern recognition tasks. In this sense, and due to the artifacts that are present in the acquisition process, the most of the biomedical images (i.e. coming from magnetic resonance tests) become noisy and it is complicated even to define a Region Of Interest (ROI) to work within.
The fuzzy Hough transform presented here implements a fuzzy version of the GHT that improves the pattern recognition results in the above referred biomedical images.
In addition to the code, some examples and demos about the 'gfht' performance of the automatic ROI identification on cardiac magnetic resonance images (CMRIs) are included. |
| MATLAB release |
MATLAB 7.9 (2009b)
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