我做了这样的作业,我必须从汽车图片中提取车牌。我不需要识别车牌号码和字母(这是同事的工作)。我必须用Matlab来做。我已经做了车牌识别部分,但现在我不能理解如何从图片中正确提取车牌部分。
你可以在下面的图片中看到我到目前为止所做的事情:
现在我不知道如何裁剪白色部分,而且应该是这样的:
我的意思是,它应该被旋转,这样它才能达到水平位置。
这是一个需要两个人完成的项目。第一个人(我)只能给第二个人任何类型的图像中的车牌,第二个人必须使用OCR。这就是教授问的问题。
我已经没有主意了。答案可能很简单,但我已经工作了一整天,就是找不到解决办法。
发布于 2015-02-09 21:53:57
注意:变量使用不同的语言,但我相信代码是可读的。很抱歉,我现在没有时间做这件事:
现在这个算法不是最好的,但它是一个起点。我现在没有时间去做它,但它肯定可以改进。例如,在底部的图像中可以看到,车牌位置填充得非常好,但在一些图片中,最后一行白色像素的长度与上面的不同,因此您最终只能得到车牌的一半。一种解决方案可以是:就在获取车牌边角之前,使所有白线的长度相同(与最长的线的长度相同)。
BW = edge(rgb2gray(imagine), 'canny');
%# hough transform
[H T R] = hough(BW);
P = houghpeaks(H, 4, 'threshold',ceil(0.75*max(H(:))));
lines = houghlines(BW, T, R, P);
% shearing transformata
slopes = vertcat(lines.point2) - vertcat(lines.point1);
slopes = slopes(:,2) ./ slopes(:,1);
TFORM = maketform('affine', [1 -slopes(1) 0 ; 0 1 0 ; 0 0 1]);
imagine2 = imtransform(imagine, TFORM);
%# show image with lines overlayed, and the aligned/rotated image
axes(handles.ImagineRotita)
imshow(imagine2);
imagineGrey = rgb2gray(imagine2);
%-----------------------------------------------------------------
axes(handles.ImaginePrel1)
imshow(imagineGrey);
imagineFiltrata = medfilt2(imagineGrey,[3 3]);
axes(handles.ImagineFilt)
imshow(imagineFiltrata);
SE = strel('disk',1);
GrayDil = imdilate(imagineGrey,SE);
GrayEr = imerode(imagineGrey,SE);
gdiff = imsubtract(GrayDil,GrayEr);
gdiff = mat2gray(gdiff);
gdiff = conv2(gdiff,[1 1;1 1]);
gdiff = imadjust(gdiff,[0.5 0.7],[0 1],0.1);
B = logical(gdiff);
er = imerode(B,strel('line',50,0));
out1 = imsubtract(B,er);
imagineSobel = imfill(out1,'holes');
H = bwmorph(imagineSobel,'thin',1);
H = imerode(H,strel('line',3,90));
final = bwareaopen(H,100);
Iprops = regionprops(final,'BoundingBox','Image');
axes(handles.ImagineSobel)
imshow(final);
imagineCuratata = imclearborder(final,18);
imagineCuratata = bwareaopen(imagineCuratata,200);
axes(handles.ImagineSobelEd)
imshow(imagineCuratata);
fileID = fopen('ImagineRezultata.txt','wb');
dlmwrite('ImagineRezultata.txt',imagineCuratata);
fclose('all');
imagineCuratata2 = imagineCuratata;
[dimX,dimY] = size(imagineCuratata2);
%-----------------------------------------------------------------
%-----------The licence plate is filled with white pixels---------
PrimPixelAlbStanga = 0;
PrimPixelAlbDreapta = 0;
Flag = 0;
for i = 1:dimX
for j = 1:dimY
if Flag == 0
if imagineCuratata2(i,j) == 1
PrimPixelAlbStanga = j;
Flag = 1;
end
end
if Flag == 1
if imagineCuratata2(i,j) == 1
PrimPixelAlbDreapta = j;
end
end
end
if PrimPixelAlbStanga > 0
for k = PrimPixelAlbStanga:PrimPixelAlbDreapta
imagineCuratata2(i,k) = 1;
end
end
PrimPixelAlbStanga = 0;
PrimPixelAlbDreapta = 0;
Flag = 0;
end
%-----------------------------------------------------------------
%-----------------------------------------------------------------
%----------The smaller lines with white pixels are removed--------
%----------this is to eliminate all the smaller lines that--------
%--------------remained for example the logo sometimes------------
PrimPixelAlbStanga = 0;
PrimPixelAlbDreapta = 0;
Flag = 0;
for i = 1:dimX
for j = 1:dimY
if Flag == 0
if imagineCuratata2(i,j) == 1
PrimPixelAlbStanga = j;
Flag = 1;
end
end
if Flag == 1
if imagineCuratata2(i,j) == 1
PrimPixelAlbDreapta = j;
end
end
end
if PrimPixelAlbStanga > 0
if (PrimPixelAlbDreapta - PrimPixelAlbStanga) < 40
for k = PrimPixelAlbStanga:PrimPixelAlbDreapta
imagineCuratata2(i,k) = 0;
end
end
end
PrimPixelAlbStanga = 0;
PrimPixelAlbDreapta = 0;
Flag = 0;
end
axes(handles.ImagineCropata)
imshow(imagineCuratata2);
%-----------------------------------------------------------------
%-----------------------------------------------------------------
%---------the corners of the licence plate are determined---------
imagineCuratata2 = bwareaopen(imagineCuratata2,500);
PrimaCoordX = 0;
PrimaCoordY = 0;
UltimaCoordX = 0;
UltimaCoordY = 0;
determinat = 0;
for i = 1:dimX
for j = 1:dimY
if imagineCuratata2(i,j) == 1
if determinat == 0
PrimaCoordX = j;
PrimaCoordY = i;
determinat = 1;
else
UltimaCoordX = j;
UltimaCoordY = i;
end
end
end
end
PrimaCoordColX = 0;
PrimaCoordColY = 0;
UltimaCoordColX = 0;
UltimaCoordColY = 0;
determinatCol = 0;
for j = 1:dimY
for i = 1:dimX
if imagineCuratata2(i,j) == 1
if determinatCol == 0
PrimaCoordColX = j;
PrimaCoordColY = i;
determinatCol = 1;
else
UltimaCoordColX = j;
UltimaCoordColY = i;
end
end
end
end
xmin = 0;
ymin = 0;
width = 0;
height = 0;
if PrimaCoordX < dimX/2
xmin = PrimaCoordX;
ymin = PrimaCoordY;
else
xmin = PrimaCoordColX;
ymin = PrimaCoordY;
end
xmin = xmin - xmin * 0.1;
ymin = ymin * 1.1;
if PrimaCoordX < dimX/2
width = UltimaCoordX - PrimaCoordX;
height = UltimaCoordY - PrimaCoordY;
else
width = UltimaCoordColX - PrimaCoordColX;
height = UltimaCoordY - PrimaCoordY;
end
rect = [xmin ymin abs(width) abs(height)];
RezultatCropat = imcrop(imagine2, rect);
axes(handles.ImagineCropataSiFilt)
imshow(RezultatCropat);
end
我所做的事情的结果可以在这些图片中看到:
发布于 2015-01-12 02:02:47
如果你试图通过物理操作图像来从任意数量的有角度的原始图像创建最终的平面化表示,这可能不是继续进行的方法。
如果您已经定义了识别车牌边界的逻辑,那么您应该能够捕捉它,然后通过OCR应用程序运行它。这将为您提供文本,然后您可以使用该文本创建一个平面图像。
现在,如果您还必须从车牌上捕获任何图形,您将需要跟踪所有可能的图形图像的数据库,然后编写一个比较/匹配例程,以便您可以识别车牌图形,但然后使用数据库中的“平面”版本来创建平面化图像,然后将OCR文本输出到该图像上。
例如,我只抓取了车牌,并在images.google.com上进行了搜索(使用他们的“按图像搜索”功能,我找到了很多可以用作模板的"flattened" versions of the image。
https://stackoverflow.com/questions/27890206
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