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

%%%%% Image Prep

% Convert To Grayscale Using the NTSC standard

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

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

figure, imshow( inputImg ), title( 'Original Image' );

%%%%% Vertical Edge Detection

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

% Do the actual detection
edges = imfilter( inputImg, mask );

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

%%%%% Edge Density Map Generation

% Create our mask of ones to add up the edge values
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

% Loop over the columns
threshold = 15; % Since this threshold can't be pre-determined, this limits
                % the generality of the code.
cleanImage = [];
for column = 1:1:size( binary, 2 )
    % Segment into regions
    [ columnLabels, num ] = bwlabel( binary(:,column) );
    
    % Create filler to sum up
    newColumn = zeros( size( columnLabels, 1 ), size( columnLabels, 2 ) );
    
    % Loop over the labels
    for labels = 1:1:num
        if size( find( columnLabels == labels ), 1 ) > threshold
            newColumn = newColumn | ( columnLabels == labels );
        end
    end 
    
    % Assemble our image one column at a time
    cleanImage = cat( 2, cleanImage, newColumn );
end

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

% Dilate the Image
se = ones( 1, 9 );
dilated = imdilate( cleanImage, se );

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

%%%%% License Plate Location


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