Fingerprint classification using a homogeneity structure of fingerprint's orientation field and neural net
D. Krasnjak, V. Krivec · International symposium on image and signal processing and analysis/ISPA ... · 2005
Fingerprint classification is important part of fingerprint identification systems that work on large databases. It provides fingerprint indexing, which results in efficient matching. This work presents usage of a homogeneity structure of fingerprint's orientation field for fingerprint indexing. The homogeneity structure is described through a quad-tree structure. A description of the quad-tree structure is the input vector for neural net that was used as a classification system. The system is tested with fingerprints of three different quality levels to provide real results.