function W = Classify(ImageFile)
% Step 1:Read image Read in
RGB = imread('C:\\test.bmp');%前提图像在该目录下
figure,
imshow(RGB),
title('Original Image');%原始图像
% Step 2:Convert image from rgb to gray
GRAY = rgb2gray(RGB);
figure,
imshow(GRAY),
title('Gray Image');%灰度图像
% Step 3:Threshold the image Convert the image to black and white in order
% to prepare for boundary tracing using bwboundaries.
threshold = graythresh(GRAY);
BW = im2bw(GRAY,threshold);
figure,
imshow(BW),
title('Binary Image');%二值图像
% Step 4:Invert the Binary Image
BW = BW;
figure,
imshow(BW),
title('Inverted Binary Image');%倒二值图像
% Step 5:Find the boundaries Concentrate only on the exterior boundaries.
% Option 'noholes' will accelerate the processing by preventing
% bwboundaries from searching for inner contours.
[B,L] = bwboundaries(BW,'noholes');
% Step 6:Determine objects properties
STATS = regionprops(L,'all'); % we need 'BoundingBox' and 'Extent'
% Step 7:Classify Shapes according to properties
% Square = 3 = (1 + 2) = (X=Y + Extent = 1)
% Rectangular = 2 = (0 + 2) = (only Extent = 1)
% Circle = 1 = (1 + 0) = (X=Y ,Extent < 1)
% UNKNOWN = 0
figure,
imshow(RGB),
title('Results');
hold on
for i = 1 :length(STATS)
W(i) = uint8(abs(STATS(i).BoundingBox(3)-STATS(i).BoundingBox(4)) < 0.1);
W(i) = W(i) + 2 * uint8((STATS(i).Extent - 1) == 0 );
centroid = STATS(i).Centroid;
switch W(i)
case 1
plot(centroid(1),centroid(2),'wO');
case 2
plot(centroid(1),centroid(2),'wX');
case 3
plot(centroid(1),centroid(2),'wS');
end
end
return
