Finger Print Recognition

 Finger print recognition, the most prominent details extraction method, uses a simple but elegant algorithm.

1. Once the image is acquired, borders are trimmed to get the core picture. Then histogram equalization is performed to increase the perceptional information.
   Matlab : imread , histeq, imadjust
2. Then image is enhanced by taking FFT on a 32 x 32 region, multiplying by the determinant of the resulting matrix and taking Fourier inverse of it.[1] Thus max frequency is enhanced and features are made consistent and any noises are suppressed.
   Matlab : fft2, ifft2, det
3. Then image is segmented for Region of Interest (ROI), thus proper orientation of the image is found and it is made erect.  Using SOBEL filters gradient along X (cosine) and Y (sine) direction are calculated and gradient of the image (tan) is obtained thereby.
4. Finally image is binaraized along the right direction and ridges and joints are searched with proper filters [2].
   Matlab : graythresh, im2bw.

Matlab: GeneralImread, Imclose, imwrite, imrotate, imshow

Matlab: PCA princomp

Matlab : Morphological functionsbwperim, imfill, bwareaopen, bwmorph

However I hope the attached article could shed more
insight into the subject.