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function [ id_codes,id_bw,code_stats,thresh,iteration ] = id_rec_process( img_gray,model,thresh,training_data_size,iteration )
narginchk(1,5)
if nargin==1
model=[];
elseif nargin<=2 || thresh==0
thresh=.68*graythresh(img_gray);
elseif nargin<=3
training_data_size=[47 31];
elseif nargin<=4 || isempty(training_data_size)
iteration=1;
end
% fprintf('Iteration %d, threshold value: %f\n',iteration,thresh)
bw=~im2bw(img_gray,thresh);
bw=imclearborder(bwareaopen(bw,10));
bwc=imdilate(bw,strel('disk',6));
code_stats=regionprops(bwc,'Area');
step_ratio=1.1;
if isempty(code_stats) && thresh*step_ratio<1
[id_codes,id_bw,code_stats,thresh,iteration]=id_rec_process(img_gray,model,thresh*step_ratio,training_data_size,iteration+1);
return
end
id_codes=blanks(18);
if isempty(code_stats)
id_bw=bw;
return
end
[~,midx]=max([code_stats.Area]);
mask=bwlabel(bwc)==midx;
id_bw=imreconstruct(mask,bw);
code_stats=regionprops(id_bw,'Image','Extent');
if length(code_stats)~=18 && thresh*step_ratio<1
[id_codes,id_bw,code_stats,thresh,iteration]=id_rec_process(img_gray,model,thresh*step_ratio,training_data_size,iteration+1);
return
end
if length(code_stats)==18
inputs=zeros(training_data_size(1)*training_data_size(2),18);
for i=1:size(inputs,2)
img=imresize(code_stats(i).Image,training_data_size);
inputs(:,i)=img(:);
end
% predict
if ~isempty(model)
try
output=model(inputs);
[~,midx]=max(output);
count=size(output,2);
for i=1:count
switch midx(i)
case 1
id_codes(i)='X';
otherwise
id_codes(i)=num2str(11-midx(i));
end
end
catch e
disp(e)
for i=1:length(e.stack)
disp(e.stack(i))
end
end
end
end
end

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