matlab - What are the best algorithms for document image thresholding in this example?

I'm trying to implement various binarization algorithms to the image shown:

Here's the code:

clc;
clear;
x=imread('n2.jpg');     %load original image

% Now we resize the images so that computational work becomes easier later onwards for us.

size(x);
x=imresize(x,[500 800]);

figure;
imshow(x);
title('original image');

z=rgb2hsv(x);       %extract the value part of hsv plane
v=z(:,:,3);
v=imadjust(v);

%now we find the mean and standard deviation required for niblack and %sauvola algorithms

m = mean(v(:))

s=std(v(:))
k=-.4;
value=m+ k*s;
temp=v;

% implementing niblack thresholding algorithm:

for p=1:1:500
    for q=1:1:800
        pixel=temp(p,q);
        if(pixel>value)

            temp(p,q)=1;
        else
            temp(p,q)=0;
        end
    end
end
figure;
imshow(temp);
title('result by niblack');
k=kittlerMet(g);

figure;
imshow(k);
title('result by kittlerMet');

% implementing sauvola thresholding algorithm:

val2=m*(1+.1*((s/128)-1));
t2=v;
for p=1:1:500
for q=1:1:800
    pixel=t2(p,q);

    if(pixel>value)
        t2(p,q)=1;
    else
        t2(p,q)=0;
    end
end

end

figure;
imshow(t2);

title('result by sauvola');

The results I obtained are as shown:

As you can see the resultant images are degraded at the darker spots.Could someone please suggest how to optimize my result??