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Human Face Recognition |
MATLAB Program 5 edge detection of 2 same alphanumeric chars | |
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%edge detection of 2 same alphanumeric chars using canny & their correlation using %corr2 function I = imread('apple1.bmp'); J= imread('apple2.bmp'); %J = imnoise(I,'salt & pepper',0.02); BW1 = im2bw(I,.5); BWA=uint8(BW1);%changes logical to uint8 BW2= im2bw(J,.5); BWB=uint8(BW2);%changes logical to uint8 BW3 = edge(BWA,'canny'); BW4 = edge(BWB,'canny'); imshow(BW3);figure; imshow(BW4);figure; %cov(count(:,1)) p=corr2(BW3,BW4); %p=BW1 * BW2; [X,Y]=meshgrid(-1:.005:1); Z=peaks(p); imshow(p);figure; %plot(Z,p); mesh(X,Y,Z); Z = fspecial('gaussian'); figure, freqz2(Z,[64 64]), axis([-1 1 -1 1 0 .8])
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First of all alphabet “A” is read twice in variables I & J then two matrices are formed BW1 & BW2 . When we are working with “canny” it is unable to handle logical values so logical value is converted to uint8 format by using uint8() function.Then edge(BW1,’canny’) function forms the sharp edges of two alphabets.Here also Gaussian filter is used in order to get the desired output thus we can conclude that they are same alphabets. h= fspecial(type) creates a two-dimensional filter h of the specified type. fspecial returns h as a correlation kernel, which is the appropriate form to use with imfilter, “type” is a string having one of these values.
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