sdirectory2 = '/Volumes/My Book/projects/pam tooth/scan b/straight adjust/';
sdirectory3 = '/Users/ecdn1g14/Desktop/straightened profiles/sls monkey data/filtered images/archaeo/sk2072/filter 1/';
sdirectory4 = '/Users/ecdn1g14/Desktop/straightened profiles/sls monkey data/filtered images/archaeo/sk2072/filter 1/binaries/';
tifFiles2 = dir([sdirectory2 '*.tif']);

NumberOfImages=length(tifFiles2);

for j=1:NumberOfImages
filename=[sdirectory2 tifFiles2(j).name];
img=imread(filename);
cem8Bit=uint8(img);
cem=im2double(cem8Bit);

%import text image and call it "cem" 
%must have steerGause.m open and be in the folder in the 'current folder'
%tab.
%cem="x"%

%perform steerable gaussian filter - must have "steerGauss.m" open.
[J,H]=steerGauss(cem,135,1);
[K,I]=steerGauss(cem,135,2);

%check if horizontal or vertical stripes have been identified
%figure(1),imshow(J);

%if they have, then create mask
mask=cem+(J.*10);
maskToSave=cem+(K.*10);

%make array of both matrices
maskArray=uint8(mask);
cemArray=uint8(cem);
%figure(2),imshow(cemArray);

%convolute images - can adjust the extent of masking by changing how much
%you divide the mask array by
%filteredCem=cemArray+(maskArray./3);
filteredCem=cem+(mask);
%filteredCem=cem+mask;
%check image
%figure(4),imshow((immultiply(cem,(mask/2))));
%figure(5),imshow(cem+(mask/2));

%isItBlank=sum(filteredCem(:));


%check mesh
%figure(4),mesh(filteredCem);

%filteredCem=imrotate(filteredCem,180);
filteredCem8Bit=uint8(filteredCem);
maskBW=im2bw(maskToSave);
%maskBW=imrotate(maskBW,180);
filename2 = [sdirectory3 tifFiles2(j).name];
dlmwrite(filename2,filteredCem);
filename3 = [sdirectory4 tifFiles2(j).name];
dlmwrite(filename3,maskBW);

end