The use of SOM for fingerprint classification
Ayad Mashaan Turky, Mohd Sharifuddin Ahmad · 2010
The use of efficient classification methods is necessary for automatic fingerprint recognition systems. This paper introduces an approach to fingerprint classification by using Self-Organizing Maps (SOM). In order to be able to deal with fingerprint images having distorted regions, the SOM learning and classification algorithms are modified. The concept of `certainty' is introduced and used in the modified algorithms. Our experiments show improved results with increasing network sizes. A network that is trained with a sufficiently large and representative set of samples can be used as an indexing mechanism for a fingerprint database, so that it does not need to be retrained for each fingerprint added to the database.