No abstract

A b s t r a c t : A s y s t e m f o r m i n u t i a e e x t r a c t i o n i n f i n g e r p r i n,t b a c k -p r o p a g a t i o n n e t w o r k s a n d G a b o r f i l t e r s i s d e s c r i b e d . F i n g e r p r i n t images a r e f i r s t convolved w i t h complex G a b o r filters a n d t h e resulting phase a n d magnitude signals a r e passed t o n e t w o r k s t o i d e n t i f y m i n u t i a r e g i o n s . P r o m i s i n g results a r e obtained with good detection r a t i o a n d low false a l a r m rate. T h e importance of h a v i n g good r e p r e s e n t a t i o n s of i m a g e d a t a t o n e u r a l n e t w o r k s i s i l l u s t r a t e d t h r o u g h v a r i a t i o n s i n p e r f o r m a n c e s of d i f f e r e n t t r a i n e d n e t w o r k s . T h e usefulness of G a b o r f i l t e r s i n t e x t u r a l i m a g e p r o c e s s i n g a n d n e u r a l n e t w o r k s i n i m a g e f e a t u r e e x t r a c t i o n a r e d e m o n s t r a t e d .

propagation networks and Gabor filters is described. Good detection ratios and low false alarm rates were achieved. The importance of having good input representations of the image data is illustrated through the variations in performances of different trained networks. The usefulness of Gabor filters in the representation processing layer is demonstrated.

No abstract

No abstract