Effect of orientation map accuracy on fingerprint classification using PCA-MSOM

Date

2000-01-01

Author

Erol, Ali
Halıcı, Uğur

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Fingerprint classification forms an important problem to be solved in identification system and there are various approaches for the solution. In any pattern classification system the most important part is the feature extraction process. For fingerprints orientation map forms the most common and promising feature to be used for classification. In this paper two different orientation map extraction algorithm are compared to find the one that gives the most reliable features for the PCA-MSOM classifier.

Subject Keywords

Neural networks, Authentication, Pattern classification, Pattern classification, Artificial neural networks, Computer vision, Biometrics, Feature extraction, Image databases, Image matching, Fingerprint recognition

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=0033645582&origin=inward
https://hdl.handle.net/11511/80633
https://www.researchgate.net/publication/3875764_The_effect_of_orientation_map_accuracy_on_fingerprint_classification_using_PCA-MSOM

Journal

International Conference on Knowledge-Based Intelligent Electronic Systems, Proceedings, KES

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

A. Erol and U. Halıcı, “Effect of orientation map accuracy on fingerprint classification using PCA-MSOM,” International Conference on Knowledge-Based Intelligent Electronic Systems, Proceedings, KES, pp. 527–530, 2000, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=0033645582&origin=inward.