Fingerprint classification with neural networks

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	Similar Articles Articles by H.V. Neto Articles by D.L. Borges

4th Brazilian Symposium on Neural Networks (SBRN '97)

Campos do Jordao, BRAZIL

December 03-December 05

ISBN: 0-8186-8070-9

	ASCII Text	x
	H.V. Neto, D.L. Borges, "Fingerprint classification with neural networks," Neural Networks, Brazilian Symposium on, pp. 66, 4th Brazilian Symposium on Neural Networks (SBRN '97), 1997.

	BibTex	x
	@article{ 10.1109/SBRN.1997.645850, author = {H.V. Neto and D.L. Borges}, title = {Fingerprint classification with neural networks}, journal ={Neural Networks, Brazilian Symposium on}, volume = {0}, year = {1997}, isbn = {0-8186-8070-9}, pages = {66}, doi = {http://doi.ieeecomputersociety.org/10.1109/SBRN.1997.645850}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Neural Networks, Brazilian Symposium on TI - Fingerprint classification with neural networks SN - 0-8186-8070-9 SP EP A1 - H.V. Neto, A1 - D.L. Borges, PY - 1997 KW - feedforward neural nets; fingerprint classification; discrete wavelet transform; feature extraction; image acquisition; image segmentation; image matching; feedforward neural networks; backpropagation VL - 0 JA - Neural Networks, Brazilian Symposium on ER -

H.V. Neto

D.L. Borges

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SBRN.1997.645850

This paper presents some intermediate results on fingerprint classification adopting a neural network as decision stage, in order to evaluate the performance of a discrete wavelet transform as feature extraction technique. Some issues on the image acquisition, preprocessing and segmentation are also discussed.

Index Terms:

feedforward neural nets; fingerprint classification; discrete wavelet transform; feature extraction; image acquisition; image segmentation; image matching; feedforward neural networks; backpropagation

Citation:

H.V. Neto, D.L. Borges, "Fingerprint classification with neural networks," sbrn, pp.66, 4th Brazilian Symposium on Neural Networks (SBRN '97), 1997

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