Fingerprint Image Enhancement Joshua Xavier Munoz- Ramos

Motivation Method for fingerprint image enhancement Ridge structure in fingerprint images are not always well defined; therefore, enhancement algorithm, is necessary A critical step in automatic fingerprint matching is extracting minutiae from the input fingerprint images. However, the performance of a minutiae extraction relies on the quality of the images.

Background Two Important ridge characteristics – Ridge ending – Ridge bifurcation

Approach 1)Original Grayscale fingerprint image 2)Local histogram equalization 3) Wiener Filtering 4)Binarization and thinning 5)Morphological and further filtering (Anisotropic Filter) 6)Enhanced binary image Fingerprint Image Enhancement: Algorithm and Performance Evaluation Lin Hong, Student Member, IEEE, Yifei Wan, and Anil Jain, Fellow, IEEE

Weiner filter W(n1,n2)=u +(v^2-n^2)/(v^2) [I(n1,n2)-u] 3x3 matrix Binary Thresholding (if I(n1,n2) > local mean set to 1 other wise set to 0)

Weiner filter / binary

Morphing/ anisotropic filter Connecting the ridges through orientation fields

Anisotropic filter Instead of using local gradients as a means of controlling the anisotropism of filters, it uses both a local intensity orientation and an anisotropic measure to control the shape of the filter. K(x0,x) = exp{-[((x-x0) n )^ 2/sig(x0)^2 + ((x-x0) n(ortho))^2/sig(x0)^2 h(x0,x) = *k(x0,x)

Results 71.1% percent FAR (using verification system ) but only tested two fingerprints with 10 different pics… 7/10 were identified False ridges endings and bifurcations Need to test more fingerprints A good image has around 40 to 50 correct ridge endings and bifurcations (different method is to apply a garbor filter ) Fingerprint acceptance rate (enhancement did not work as well as expected) Picture was clearer to see after enhancement, and the filters did smooth out noise However many false ridges and bifurcations Many parts where the picture was not clear my enhancement did not work. Future work…. Fix the orientation field and the anisotropic filter.. Many details were lost. (citation)