function [ outputImg ] = isolatePlate( inputImg )
% ISOLATEPLATE Draw a box around a license plate in the input image
%  More info.



% Params
%SIZE_THRESHOLD = 60;
TRUE = 1;
FALSE = 0;


% Show the original
inputImg = im2double( inputImg );
%figure, imshow( inputImg ), title( 'Original Image' );



%%%%% Image Prep

% Convert To Grayscale Using the NTSC standard

red = immultiply( inputImg(:,:,1), 299 );
green = immultiply(  inputImg(:,:,2), 587 );
blue = immultiply( inputImg(:,:,3), 114 );

newImg = red + green + blue;
newImg = imdivide( newImg, 1000 );



% Smooth the image
smoother = ones( 6, 6 );
newImg = imfilter( newImg, smoother );
newImg = imdivide( newImg, 36 );

%figure, imshow( newImg ), title( 'Grayscale Image' );

flipImg = rot90( newImg );








% create a new light gray image so we can see the boxes.
lightGray = imdivide( newImg, 4 );
lightGray = imadd( lightGray, 0.749 );

% % Find the center of the red data, to find the column that the license
% % plate should cross
% 
% scaledRed = mat2gray( red );
% scaledBlue = mat2gray( blue );
% scaledGreen = mat2gray( green );
% 
% % threadhold the red values...
% redMap = scaledRed > 0.30 & scaledGreen < 0.40 & scaledBlue < 0.40;
% 
% se = strel( 'disk', 5 );
% redMap = imclose( redMap, se );
% 
% [row,column] = find( redMap );
% redColumn = sum( column ) / size( column, 1 );
% redRow = sum( row ) / size( row, 1 );
% 
% figure, imshow( imcomplement( redMap ) ), title( 'Red Map' );
% rectangle( 'Position', [ redColumn 1 1 size( red, 1 ) ] );
% rectangle( 'Position', [ 0 redRow size( red, 2 ) 1 ] );

%%%%% Vertical Edge Detection

% Create our mask - a Sobel for vertical edge detection
mask = fspecial( 'sobel' );
mask = rot90( mask, 1 );

% Do the actual detection
vEdges = imfilter( newImg, mask );
hEdges = rot90( imfilter( flipImg, mask ), -1 );

vEdgesScaled = immultiply( vEdges, 0.7 );
hEdgesScaled = immultiply( hEdges, 0.3 );
edges = imadd( vEdgesScaled, hEdgesScaled );

% Show what we have so far
%figure, imshow( vEdges ), title( 'Vertical Edges' );
%figure, imshow( hEdges ), title( 'Horizontal Edges' );
%figure, imshow( edges ), title( 'Edges' );

%%%%% Edge Density Map Generation

% Create our mask of ones to add up the edge values
%densityMask = ones( 3, 15 );
densityMask = ones( 3, 15 );

% Sum it up
edgeMap = imfilter( edges, densityMask );
edgeMap = imdivide( edgeMap, 45 );

% Show what we have so far
%figure, imshow( edgeMap ), title( 'Edge Map' );



%%%%% Binarization / Clean Up / Dilation

% Binarize!!!!  Use Otsu's Method.  It's fast.
level = graythresh( edgeMap );
binary = im2bw( edgeMap, level );

% Show what we have so far
%figure, imshow( binary ), title( 'Binarized Edge Map' );

% Clean Up by getting rid of small horizontal lines

se = strel( 'disk', 2 );
cleanImage = imopen( binary, se );

% Show what we have so far
%cleanImage = binary; % skipping the clean up step...don't seem to need it
%figure, imshow( cleanImage ), title( 'Cleaned Image' );

% Dilate the Image
%se = ones( 1, 9 );
%se = ones( 100, 100 );
se = strel( 'disk', 13 );
dilated = imdilate( cleanImage, se );

% Show what we have so far
%figure, imshow( dilated ), title( 'Dilated Image' );



%%%%% License Plate Location

% find all the 8-connected regions in the dilated binary image
[labeled, num] = bwlabel( dilated );

% Feature Extraction
% here we will loop through the dilated image...
info = [];
imgWidth = size( newImg, 2 );
imgHeight = size( newImg, 1 );

for k = 1:1:num
    % get the indices of one connected region (current k value for this
    % iteration)
    [row,column] = find( labeled == k );
    
    % get the top left row&column
    topLeftRow = min( row );
    topLeftColumn = min( column );
    
    % BR row&column
    bottomRightRow = max( row );
    bottomRightColumn = max( column );
    
    % get the size of...yeah...
    numPixels = size( row, 1 );
    
    % numbers!
    width = bottomRightColumn - topLeftColumn + 1;
    height = bottomRightRow - topLeftRow + 1;
    
    % Check whether the box is within another box
    
    % structure of each row: TL row, TL col, BR row, BR col, numpixels,
    % width, height.  Note that it's 7 columns...
    newRow = [ topLeftRow topLeftColumn bottomRightRow bottomRightColumn numPixels width height ];
    

    % add it to our dater structure to store it!
    ratio = width / height;
    area = width * height;
    
    % check aspect ratio
    if ( ratio > 1.3 & ratio < 2.35 )
        % check min. size through area
        if ( area > 16000 )
            % check max size through percent of image
            if ( width < 0.7 * imgWidth & height < 0.7 * imgHeight )
                info = cat( 1, info, newRow );
            end
        end
    end
end



%%%% If we still have more than one box, then try to filter some more
sums = [];
if ( size( info, 1 ) > 1 )
    % Take a slice of the remaining boxes
    sliceHeight = 4;
    sliceImg = zeros( size( inputImg, 1 ), size( inputImg, 2 ) );
    for k = 1:1:size( info, 1 )
        row = info( k, : );
        sliceWidth = row( 6 );
        sliceX = row( 2 );
        sliceY = ( row( 7 ) / 2 ) - ( sliceHeight / 2 ) + row( 1 );
        
        sliceImg( sliceY:sliceY + sliceHeight, sliceX:sliceX + sliceWidth ) = 1;
        
        % sum up what's in our slice
        slice = vEdges( sliceY:sliceY + sliceHeight, sliceX:sliceX + sliceWidth );
        slice = slice > graythresh( slice );
        figure, imshow( slice );
        edgeResponse = sum( sum( slice ) );

        sums = cat( 1, sums, edgeResponse );
    end
    
    sliceImg = immultiply( double( sliceImg ), vEdges );
    figure, imshow( sliceImg ), title( 'Slices' );
    
    %%%% Filter based on slices
    [ component, index ] = max( sums );
    info
    sums
    component
    index
    info = info( index, : );
end





%%%% Draw our boxes that we have left
figure, imshow( inputImg ), title( 'Original Image - With Boxes' );
for k = 1:1:size( info, 1 ) 
    row = info( k, : );
    %     1          2            3                4               5         6     7
    % [ topLeftRow topLeftColumn bottomRightRow bottomRightColumn numPixels width height ];
%    rectangle( 'Position', [ row( 2 ) row( 1 ) row( 6 ) row( 7 ) ] ); 
    inputImg = drawrectangle( inputImg, row( 2 ), row(1), row( 6 ), row(7), 1, 0, 0 );
end


% now return the processed image...
outputImg = inputImg;