Title of Activity :
- Extracting the image of license plate
Objective :
- To locate the vehicle license`s plate.
Content / Procedure :
- Adding some source code to eliminating the noise.
Result / Analysis :
- The process contains each phase performs a segmentation process on the grey image to eliminate the redundant pixels that don`t belong to a plate region.
clear all; close all; clc;
% Threshold
LLimit_Density = 0.20;
HLimit_Density = 1.50;
LLimit_Area = 30;
HLimit_Area = 2000;
LLimit_HWratio = 0.3;
HLimit_HWratio = 9.5;
LLimit_TotalArea = 400;
HLimit_TotalArea = 3000;
% Display result
DisplayGrayImage = 1;
DisplayMedianFiltering = 1;
DisplayHorizontalProfile = 1;
DisplayVerticalProfile = 1;
% Get a list of all the images name in folder images
InputImg = imread('images\499.JPG');
InputImg = im2double( InputImg );
% Convert To Grayscale Using the NTSC standard
red = immultiply( InputImg(:,:,1), 299 );
green = immultiply( InputImg(:,:,2), 587 );
blue = immultiply( InputImg(:,:,3), 114 );
ProcessImg = red + green + blue;
ProcessImg = imdivide( ProcessImg, 1000 );
if DisplayGrayImage == 1
figure; hold on; imshow( ProcessImg );
end
% Perform median filtering to remove noise
ProcessImg = medfilt2(ProcessImg, [5 5]);
if DisplayMedianFiltering == 1
figure; hold on; imshow( ProcessImg );
end
I = ProcessImg;
if ~(isa(I,'double') || isa(I,'single')); I = im2single(I); end
gh = imfilter(I,fspecial('sobel') ,'replicate');
gv = imfilter(I,fspecial('sobel')','replicate');
EdgeImg = abs(gh) + abs(gv);
%figure, imshow(EdgeImg);
% Create horizontal profile
HProfile = sum(EdgeImg,2);
H_thres = mean(HProfile);
[ Filtered_HProSegment ] = ProfileSegmentation( HProfile, H_thres*0.75, 15);
if DisplayHorizontalProfile == 1
clear rgb_img;
rgb_img(:,:,1) = uint8(EdgeImg * 255);
rgb_img(:,:,2) = uint8(EdgeImg * 255);
rgb_img(:,:,3) = uint8(EdgeImg * 255);
for i=1:size(Filtered_HProSegment,1)
for j=1:size(rgb_img,2)
rgb_img(Filtered_HProSegment(i,1),j,1) = 255;
rgb_img(Filtered_HProSegment(i,1),j,2) = 0;
rgb_img(Filtered_HProSegment(i,1),j,3) = 0;
rgb_img(Filtered_HProSegment(i,2),j,1) = 255;
rgb_img(Filtered_HProSegment(i,2),j,2) = 0;
rgb_img(Filtered_HProSegment(i,2),j,3) = 0;
end
end
figure; imshow(rgb_img);
end
% Find the Horizontal Density Vector
HDV = zeros(size(Filtered_HProSegment,1), size(EdgeImg,2));
M = 150;
for k=1:size(Filtered_HProSegment,1)
SlidingWindowsArea = (Filtered_HProSegment(k,2) - Filtered_HProSegment(k,1)) * M;
for width_cnt = 1:size(EdgeImg,2)
min_w = width_cnt - M;
max_w = width_cnt + M;
if min_w < 1
min_w = 1;
end
if max_w > size(EdgeImg,2)
max_w = size(EdgeImg,2);
end
%SlidingWindowsArea = (max_w - min_w )* M;
SumG = sum(sum(EdgeImg(Filtered_HProSegment(k,1):Filtered_HProSegment(k,2), min_w:max_w)));
HDV(k,width_cnt) = SumG/SlidingWindowsArea;
end
V_thres = mean(HDV(k,:));
FoundProfile = ProfileSegmentation( HDV(k,:)', V_thres, 100);
VProSegment{k}.Profile = [];
if size(FoundProfile,1) > 0
VProSegment{k}.Profile = FoundProfile;
end
end
if DisplayVerticalProfile == 1
clear rgb_img;
rgb_img(:,:,1) = uint8(EdgeImg * 255);
rgb_img(:,:,2) = uint8(EdgeImg * 255);
rgb_img(:,:,3) = uint8(EdgeImg * 255);
figure; imshow(rgb_img); hold on;
for i=1:size(Filtered_HProSegment,1)
if isempty(VProSegment{i}.Profile) == 0
for j=1:size(VProSegment{i}.Profile,1)
x = VProSegment{i}.Profile(j,1);
y = Filtered_HProSegment(i,1);
w = VProSegment{i}.Profile(j,2) - VProSegment{i}.Profile(j,1);
h = Filtered_HProSegment(i,2) - Filtered_HProSegment(i,1);
rectangle('Position',[x,y,w,h], 'EdgeColor', 'Red', 'LineWidth',2)
end
end
end
end
% Auto-skew correction
level = graythresh(InputImg);
BW_ProcessImg = im2bw(InputImg,level);
for i=1:size(Filtered_HProSegment,1)
if isempty(VProSegment{i}.Profile) == 0
for j=1:size(VProSegment{i}.Profile,1)
x1 = VProSegment{i}.Profile(j,1);
y1 = Filtered_HProSegment(i,1);
x2 = VProSegment{i}.Profile(j,2);
y2 = Filtered_HProSegment(i,2);
ProcessImgSegment = BW_ProcessImg(y1:y2, x1:x2);
EdgeSegment = EdgeImg(y1:y2, x1:x2);
level = graythresh(EdgeSegment);
BW = im2bw(EdgeSegment,level*0.2);
BW1 = imfill(BW,'holes');
cc = bwconncomp(BW1);
stats = regionprops(BW1, 'Area', 'FilledImage');
SumBW = 0;
for cnt =1:size(stats,1)
SumBW = SumBW + stats(cnt).Area;
end
MeanBW = SumBW/size(stats,1);
idx = find([stats.Area] > MeanBW*0.2);
BW2 = ismember(labelmatrix(cc), idx);
se = strel('disk',5);
BW2 = imclose(BW2,se);
%figure; imshow(BW2);
% Find the skew angle by using hough transform
%BW22 = edge(BW2,'canny');
[H,T,R] = hough(BW2);
P = houghpeaks(H,5,'threshold',ceil(0.3*max(H(:))));
lines = houghlines(BW2,T,R,P,'FillGap',5,'MinLength',7);
DetectedSkew = 0;
if isempty(fieldnames(lines)) == 0
max_len = 0;
max_ind = 0;
for cnt =1:size(lines,2)
len = norm(lines(cnt).point1 - lines(cnt).point2);
if ( len > max_len)
max_len = len;
max_ind = cnt;
end
end
DetectedSkew = lines(max_ind).theta;
end
% Deskew the car plate image
if DetectedSkew == 0
tf = [1 0 0; 0 1 0; 0 0 1];
else
tf = [1 tand(90 - DetectedSkew) 0; 0 1 0; 0 0 1];
end
tform = maketform('affine', tf);
BW3 = imtransform(BW2 & ProcessImgSegment, tform);
se = strel('disk',1);
BW3 = imerode(BW3,se);
%figure; imshow(BW3);
cc = bwconncomp(BW3);
stats = regionprops(BW3, 'ConvexHull', 'Area', 'BoundingBox');
% Check the properties
fig_BW_disp = figure;
for cnt = 1:size(stats,1)
BW_disp = BW3;
clf(fig_BW_disp);
figure(fig_BW_disp); imshow(BW_disp); hold on;
rectangle('Position',stats(cnt).BoundingBox,'EdgeColor','red','LineWidth',2);
HWratio = (stats(cnt).BoundingBox(4)/stats(cnt).BoundingBox(3))
density = stats(cnt).Area / (stats(cnt).BoundingBox(3)*stats(cnt).BoundingBox(4))
area = stats(cnt).Area
pause
end
% Condition: Check the density
TotalArea = 0;
idx = [];
for cnt = 1:size(stats,1)
HWratio = (stats(cnt).BoundingBox(4)/stats(cnt).BoundingBox(3));
density = stats(cnt).Area / (stats(cnt).BoundingBox(3)*stats(cnt).BoundingBox(4));
area = stats(cnt).Area;
if(density > LLimit_Density) && (density < HLimit_Density) ...
&& (area > LLimit_Area) && (area < HLimit_Area) ...
&& (HWratio > LLimit_HWratio) && (HWratio < HLimit_HWratio)
idx = [idx cnt];
TotalArea = TotalArea + area;
end
end
BW4 = ismember(labelmatrix(cc), idx);
cc = bwconncomp(BW4);
if (TotalArea > LLimit_TotalArea) && (TotalArea < HLimit_TotalArea) ...
%&& (cc.NumObjects >= LLimit_NumOfCharacter) && (cc.NumObjects <= HLimit_NumOfCharacter)
figure; imshow(BW4);
end
end
end
end
- Get the illustrates an edge detection process.
Conclusion.
- Through this process, I can detect few factors contribute to this process failed which is :
a) Shining of surface plate.
b) A dirty plate surface.
c) Damaged of surface plate.
- Need more magic image to get successful result.
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