I have an application which takes data from the fingerprint device. There are 3 steps for the Finger Minutiae Extraction:
I am done with the Image binarization and Image thinnig part. Now I have implemented code for the Minutiae Extraction. Code look like this:
byte[][] outSkeleton = BasicOperations.copy(fingerprint.getSkeleton());
int margin = 50;
int bif = 0;
int eol = 0;
for(int i=margin+20; i<width-margin-20; i++){
for(int j=margin; j<height-margin; j++){
int patterns = BasicOperations.timesPattern01(i,j,fingerprint.getSkeleton());
if(fingerprint.getSkeleton()[i][j]==1){
if(patterns==1){
outSkeleton = drawRectangle(i,j,outSkeleton,2);
eol++;
}
if(patterns==3){
outSkeleton = drawRectangle(i,j,outSkeleton,3);
bif++;
}
}
}
}
..........
public static int timesPattern01(int i, int j, byte[][] image){
int pattern01 = 0;
//Counting threads[0,1]
if(image[i-1][j]==0 && image[i-1][j+1]==1) pattern01++;
if(image[i-1][j+1]==0 && image[i][j+1]==1) pattern01++;
if(image[i][j+1]==0 && image[i+1][j+1]==1) pattern01++;
if(image[i+1][j+1]==0 && image[i+1][j]==1) pattern01++;
if(image[i+1][j]==0 && image[i+1][j-1]==1) pattern01++;
if(image[i+1][j-1]==0 && image[i][j-1]==1) pattern01++;
if(image[i][j-1]==0 && image[i-1][j-1]==1) pattern01++;
if(image[i-1][j-1]==0 && image[i-1][j]==1) pattern01++;
return pattern01;
}
.....
private static byte[][] drawRectangle(int x, int y, byte[][] skeleton, int color){
int size = 3;
for(int i=-size; i<=size; i++){
skeleton[x-i][y+size] = (byte)color;
skeleton[x+i][y-size] = (byte)color;
skeleton[x-size][y+i] = (byte)color;
skeleton[x+size][y-i] = (byte)color;
}
return skeleton;
}
But this code calculate around average 300 END OF LINES
. It takes into account every end of line point.
Could any one help me to optimize the code?
So the reason for this is, while getting the minutiae map false minutiae are also detected. So after getting the minutiae we have to remove the false minutiae from the minutiae map.
Types of false minutiae:
In addition a large number of false minutiae are always detected close to the boundary of the region of interest (boundary effect).
So for removing these false minutiae there are various algorithms defined. One of them is defined in this link.
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