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* Project Name:   Fingerprint Recognition Project- Implementation Code
* Programmer:   msi_333
* Type:   Security
* Technology:  Matlab
* IDE:   Matlab
 Description:   Includes steps such as : Binarization, Normalization, Segmentation, Principal component analysis (PCA) , remove Noise, reduce Resolution
Code.
Attachment:
101.JPG
101.JPG [ 24.29 KiB | Viewed 19667 times ]

Code sample :
matlab code
function menutiaeTable=Finger_Print(originalImg)


img=imread(originalImg);

segImage=Segmentation(img);
normImage=Normalization(segImage);
enhancedImg=removeNoise(normImage);
binaryImg=binnary(enhancedImg,17 ,2.24 , 0.85 );%Binarization(enhancedImg);
thinningImg=bwmorph(1-binaryImg,'thin',Inf);
[menutiaeImg, menutiaeTable]=menutieaExtraction(thinningImg);


figure
imshow(enhancedImg),title('Image After Remove Noise');
figure
imshow(binaryImg),title('Image After Binarization');
figure
imshow(1-thinningImg),title('Image After Thinning(Skelton)');
figure;
imshow(menutiaeImg),title('Image Ridges White(ending)-Blue(Bifiraction)');

lable='Image After Remove Noise and Ridges';
margeImg(enhancedImg, menutiaeTable, lable)

lable='Image After Binarization and Ridges';
margeImg( binaryImg, menutiaeTable, lable)

lable='Thinning(Skelton) Image and Ridges';
margeImg( 1-thinningImg, menutiaeTable, lable)


Reduce Image resolution
matlab code
function reducedResImg=reduceReselution(img)

[W,H]=size(img) ;

for i=1:1:floor(W/2) ;
for j=1:1:floor(H/2) ;
reducedResImg(i,j)=img(i*2,j*2) ;
end
end

Binarization:
matlab code
function binary=Binarization(img)

globalThresh=graythresh(img);

[H W]=size(img);

for i=1:H
for j=1:W

if(img(i,j)>=globalThresh)
binary(i,j)=1;
else
binary(i,j)=0;
end
end
end





Attachments:
File comment: Finger Print Classification
FingerPrint project.zip [403.76 KiB]
Downloaded 4890 times

_________________
M. S. Rakha, Ph.D.
Queen's University
Canada
Author:
Mastermind
User avatar Posts: 2715
Have thanks: 74 time
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