Question

我正在实施霍夫圆变换并在仅包含一个圆周的二进制图像上尝试我的代码，但是对于任何半径，我尝试获得相同数量的累积点，这里是代码：

y0array, x0array= np.nonzero(image1)

r=8    

acc_cells = np.zeros((100,100), dtype=np.uint64)

for i in range( len(x0array)):
    y0= y0array[i]
    x0= x0array[i]

    for angle in range(0,360): 
        b = int(y0 - (r * s[angle]) ) //s is an array of sine of angles from 0 to 360
        a = int(x0 - (r * c[angle]) ) //c is an array of cosine of angles from 0 to 360

        if a >= 0 and a < 100 and b >= 0 and b < 100:

            acc_cells[a, b] += 1


acc_cell_max = np.amax(acc_cells)
print(r, acc_cell_max)

为什么会出现这种情况？

Answer 1

你必须像你一样找到圆圈的中心。你必须找到每个边坐标

您可以在 detectCircles 函数中检查hough circle的python实现 https://github.com/PavanGJ/Circle-Hough-Transform/blob/master/main.py

另外，请参考matlab函数的hough circle实现

http://www.mathworks.com/matlabcentral/fileexchange/4985-circle-detection-via-standard-hough-transform

function [y0detect,x0detect,Accumulator] = houghcircle(Imbinary,r,thresh)
%HOUGHCIRCLE - detects circles with specific radius in a binary image. This
%is just a standard implementaion of Hough transform for circles in order
%to show how this method works.
%
%Comments:
%       Function uses Standard Hough Transform to detect circles in a binary image.
%       According to the Hough Transform for circles, each pixel in image space
%       corresponds to a circle in Hough space and vise versa. 
%       upper left corner of image is the origin of coordinate system.
%
%Usage: [y0detect,x0detect,Accumulator] = houghcircle(Imbinary,r,thresh)
%
%Arguments:
%       Imbinary - A binary image. Image pixels with value equal to 1 are
%                  candidate pixels for HOUGHCIRCLE function.
%       r        - Radius of the circles.
%       thresh   - A threshold value that determines the minimum number of
%                  pixels that belong to a circle in image space. Threshold must be
%                  bigger than or equal to 4(default).
%
%Returns:
%       y0detect    - Row coordinates of detected circles.
%       x0detect    - Column coordinates of detected circles. 
%       Accumulator - The accumulator array in Hough space.
%
%Written by :
%       Amin Sarafraz
%       Computer Vision Online 
%       http://www.computervisiononline.com
%       amin@computervisiononline.com
%
% Acknowledgement: Thanks to CJ Taylor and Peter Bone for their constructive comments
%
%May 5,2004         - Original version
%November 24,2004   - Modified version,faster and better performance (suggested by CJ Taylor)
%Aug 31,2012        - Implemented suggestion by Peter Bone/ Better documentation 


if nargin == 2
    thresh = 4; % set threshold to default value
end

if thresh < 4
    error('HOUGHCIRCLE:: Treshold value must be bigger or equal to 4');
end

%Voting
Accumulator = zeros(size(Imbinary)); % initialize the accumulator
[yIndex xIndex] = find(Imbinary); % find x,y of edge pixels
numRow = size(Imbinary,1); % number of rows in the binary image
numCol = size(Imbinary,2); % number of columns in the binary image
r2 = r^2; % square of radius, to prevent its calculation in the loop

for cnt = 1:numel(xIndex)
    low=xIndex(cnt)-r;
    high=xIndex(cnt)+r;

    if (low<1) 
        low=1; 
    end

    if (high>numCol)
        high=numCol; 
    end

    for x0 = low:high
        yOffset = sqrt(r2-(xIndex(cnt)-x0)^2);
        y01 = round(yIndex(cnt)-yOffset);
        y02 = round(yIndex(cnt)+yOffset);

        if y01 < numRow && y01 >= 1
            Accumulator(y01,x0) = Accumulator(y01,x0)+1;
        end

        if y02 < numRow && y02 >= 1
            Accumulator(y02,x0) = Accumulator(y02,x0)+1;
        end
    end
end

% Finding local maxima in Accumulator
y0detect = []; x0detect = [];
AccumulatorbinaryMax = imregionalmax(Accumulator);
[Potential_y0 Potential_x0] = find(AccumulatorbinaryMax == 1);
Accumulatortemp = Accumulator - thresh;
for cnt = 1:numel(Potential_y0)
    if Accumulatortemp(Potential_y0(cnt),Potential_x0(cnt)) >= 0
        y0detect = [y0detect;Potential_y0(cnt)];
        x0detect = [x0detect;Potential_x0(cnt)];
    end
end

霍夫圆变换实现

1 个答案: