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一、Combined Separability Filter
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二、部分代码
clear;
X = imread(‘testimages/sample1.png‘); % sample1.png is a gray-scale CG generated face image
[H, W] = size(X);
S1 = cat(3,X,X,X); % used for displaying final result (Geometric mean)
S2 = cat(3,X,X,X); % used for displaying final result (Arithmetic mean)
X = double(X); % convert data type to double
I1 = cvtIntegralImage(X); % calculate integral image
P1 = cvtIntegralImage(X.^2); % calculate integral image of squared pixel value
I2 = cvtIntegralImage45(X); % calculate 45 degrees integral image
P2 = cvtIntegralImage45(X.^2); % calculate 45 degrees integral image of squared pixel value
nR = 3; % filter size parameter
nTH = 0.55; % threshold for finding local peaks
P = zeros(H,W,4); % variable to store separability map
P(:,:,1:2) = cvtCombSimpRectFilter(I1,P1,nR); % apply vertical and horizontal rectangular filters
P(:,:,3:4) = cvtCombSimpRectFilter45(I2,P2,nR); % apply diagonal left and right filters
P(P<0) = 0;
finalMap1 = prod(P(:,:,:),3).^(1/4.0);
finalMap2 = mean(P(:,:,:),3);
figure(10);clf;
for i=1:6
subplot(2,4,i);
if (i < 5)
imagesc(P(:,:,i));
axis equal tight;
title([‘separability map #‘ num2str(i)]);
elseif (i==5)
imagesc(finalMap1);
axis equal tight;
title(‘Geometric mean‘);
elseif (i==6)
imagesc(finalMap2);
axis equal tight;
title(‘Arithmetic mean‘);
end
end
% find local peaks (Geometric mean)
PL1 = cvtFindLocalPeakX(finalMap1,1,nTH);
% draw circle and cross at each local peak with radius of the filter (nR)
for H=1:size(PL1,2)
S1 = cvtDrawCircle(S1, PL1(2,H),PL1(1,H),nR,[255,0,0],20);
S1 = cvtDrawCross(S1,PL1(2,H),PL1(1,H),nR,[255,255,255]);
end
subplot(2,4,7);
image(S1); % display original
title({[‘Local peaks > ‘ num2str(nTH)]; ‘Geometric mean‘});
axis equal tight;
% find local peaks (Arithmetic mean)
PL2 = cvtFindLocalPeakX(finalMap2,1,nTH);
% draw circle and cross at each local peak with radius of the filter (nR)
for H=1:size(PL2,2)
S2 = cvtDrawCircle(S2, PL2(2,H),PL2(1,H),nR,[255,0,0],20);
S2 = cvtDrawCross(S2,PL2(2,H),PL2(1,H),nR,[255,255,255]);
end
subplot(2,4,8);
image(S2); % display original with marks for the local peak
axis equal tight;
title({[‘Local peaks > ‘ num2str(nTH)]; ‘Arithmetic mean‘});
三、仿真结果
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四、参考文献
[1] Y. Ohkawa, C. H. Suryanto, K. Fukui, "Fast Combined Separability Filter for Detecting Circular Objects", The twelfth IAPR conference on Machine Vision Applications (MVA) pp.99-103, 2011.
[2] K. Fukui, O. Yamaguchi, "Facial feature point extraction method based on combination of shape extraction and pattern matching", Systems and Computers in Japan 29 (6), pp.49-58, 1998.
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【图像检测】基于Combined Separability Filter实现鼻孔和瞳孔检测matlab源码