Niblack---二值化算法 - cxf7394373的专栏 - CSDN博客
Niblack---二值化算法 收藏
Niblack二值化算法是比较简单的局部阈值方法，阈值的计算公式是T = m + k*v，其中m为以该像素点为中心的区域的平均灰度值，v是该区域的标准差，k是一个系数，matlab程序如下：
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I = imread('card3.bmp');
I = rgb2gray(I);
w = 2;%
max = 0;
min = 0;
[m,n] = size(I);
T = zeros(m ,n );
%
for i = (w + 1):(m - w)
for j = (w + 1):(n - w)
sum = 0;
for k = -w:w
for l = -w:w
sum = sum + uint32(I(i + k,j + l));
end
end
average = double(sum) /((2*w+1)*(2*w+1));
s = 0;
for k = -w:w
for l = -w:w
s = s + (uint32(I(i + k,j + l)) - average)*(uint32(I(i + k,j + l)) - average);
end
end
s= sqrt(double(s)/((2*w+1)*(2*w+1)));
T(i,j) = average + 0.2*s;
end
end
for i = 1:m
for j = 1:n
if I(i,j) > T(i,j)
I(i,j) = uint8(255);
else
I(i,j) = uint8(0);
end
end
end
imshow(I);
I = imread('card3.bmp');
I = rgb2gray(I);
w = 2;%
max = 0;
min = 0;
[m,n] = size(I);
T = zeros(m ,n );
%
for i = (w + 1):(m - w)
for j = (w + 1):(n - w)
sum = 0;
for k = -w:w
for l = -w:w
sum = sum + uint32(I(i + k,j + l));
end
end
average = double(sum) /((2*w+1)*(2*w+1));
s = 0;
for k = -w:w
for l = -w:w
s = s + (uint32(I(i + k,j + l)) - average)*(uint32(I(i + k,j + l)) - average);
end
end
s= sqrt(double(s)/((2*w+1)*(2*w+1)));
T(i,j) = average + 0.2*s;
end
end
for i = 1:m
for j = 1:n
if I(i,j) > T(i,j)
I(i,j) = uint8(255);
else
I(i,j) = uint8(0);
end
end
end
imshow(I);
上述程序中选择的窗口大小是5*5，处理结果不好，产生了大量的噪声...
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