Hough Transform 3D

Circle detection with Hough Transform in GUI

Hough Transform using 3D matrix. Is a GUI.
Use the general Hough tranform.
Written by M.Sc. Guillermo García Jiménez, descripted into the posgrade project: Circularity of digital images.
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~~In the Gui works for graphs:~~
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++Image: show the original image.
++Circles detected: show the circles detected in original image and draw the circles.
++Matrix Accumulator: show the votes into Acc matrix for parameters h,k in two views (2D, 3D).
++Radius histogram: show all radios founded in the image.
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++import image (button): you can load the image.
++Initial conditions (checkbox, select before to load the image):
------------radius rank:the user can delimit the radius. The values allow for rmin is 10 pixels, and for the
rmax=inf[[max{rows/2, columns/2}] pixels.
------------number of circles: this is good when the user knows a prior the number of circles into image or needs the
circles with more votes.
------------search region: specify the local radio (when the search is by locality ) or dimensions of squad area (when
the search is by umbral) for to found the local maximas.
NOTE:
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****The formats allow are: .jpg, .png; the images must be in grayscale, binary or RGB.
****The matrix must be represented by integer values and single, double, uint8 or uint16.
****The image loaded should not have much noise. In all case, is recomendable apply pre processing before to
analyze the image.
****The circle detection is limited in a standard rank (by default), with interval [rmin, rmax], fulfill the next sentence:
rmin= 10 pixels, rmax=inf[max{rows/2, columns/2}] pixels
where: rows and columns are reference to size of matrix that descripted the image.
****The program does not detect circumferences with center outside the image domain.
References:
Nixon, M.S., and Aguado, A.S. (2008). Feature extraction and image processing for
computer vision. 2nd Edition, Academic Press, Elsevier.