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The use of SOM for fingerprint classification

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...

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Bibliographic Details
Main Authors: Turky A.M., Ahmad M.S.
Other Authors: 25825717300
Format: Conference paper
Published: 2023
Subjects:
Biometric
Fingerprint classification
Self organizing maps
Biometrics
Conformal mapping
Image recognition
Information retrieval
Knowledge management
Learning algorithms
Automatic fingerprint recognition system
Classification algorithm
Classification methods
Fingerprint database
Fingerprint images
Indexing mechanisms
Modified algorithms
Network size
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Summary: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. �2010 IEEE.

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