/Fingerprint-Recognition

Pattern Recognition class project

First we will convert images to greyscale as RGB(x,y)= (R(x,y)+G(x,y)+B(x,y))/3 then, follow these steps:

Steps

Thinning process & generating the Skeleton:

Based on the “A Fast Parallel Algorithm for Thinning Digital Patterns” by T. Y. Zhang & C.Y. Suen, for each center point P1, it's neighboring cells will be defined by:

definning points

We go through all center cells and see which cells to re-color as Black/1 based on these conditions:

  • 3 <= B(P1)= P2+P3+P4+P5+P6+P7+P8+9 <= 6

  • A(P1)= 1; center point must be Black/1 itself!

  • FOR EVEN iterations ((x+y)%2==0):

  • P2P4P6=0

  • P4P6P8=0 , where (*) indicates ANDing or multiplying!

  • FOR OLD iterations ((x+y)%2==1):

  • P2P4P8=0

  • P2P6P8=0 , where (*) indicates ANDing or multiplying!

Minutiae extraction using Rutovitz’s Crossing-Number:

Left/Top trimming before it might help?!

For each center point (P), values are calculated by: Defining CN CN Values

Comparing:

It's easy to create array of nodes where each has X,Y,Type & Types of neighboring cells but somehow I'm running out of heap space here even before comparing! .:. I'm picking the nears X,Y cell with similar type!

References: