A Novel Hybrid FLANN-PSO Technique for Real Time Fingerprint Classification.
In this paper we are presenting a Particle swarm optimized functional link neural network for classifying a collection of real time fingerprints in the field of biometric recognition. From the collected fingerprints the feature vectors are extracted as a collection of different angle oriented featur...
| Publicado en: | Medico-Legal Update Vol. 19; no. 2; pp. 740 - 747 |
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| Autores principales: | , |
| Formato: | equations & formulas pictorial tables/charts Journal Article |
| Publicado: |
Institute of Medico-legal publications Pvt Ltd
Jul-Dec2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=138233373&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 138233373 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0971720X 6CKZ jtl: Medico-Legal Update issn: 0971720X maglogo: N pubinfo: dt: Jul-Dec2019 vid: 19 iid: 2 pid: 50801 pub: Institute of Medico-legal publications Pvt Ltd artinfo: ui: 138233373 138233373 138233373 10.5958/0974-1283.2019.00265.2 138233373 ppf: 740 ppct: 7 formats: tig: atl: A Novel Hybrid FLANN-PSO Technique for Real Time Fingerprint Classification. aug: au: Mishra, Annapurna Dehuri, Sachidananda affil: Dept. of Electronics and Communication Engineering, Silicon Institute of Technology, Silicon Hills, Patia, Bhubaneswar, Odisha, India sug: subj: Fingerprints Classification Biometrics Neural Networks (Computer) Methods Algorithms Artificial Intelligence ab: In this paper we are presenting a Particle swarm optimized functional link neural network for classifying a collection of real time fingerprints in the field of biometric recognition. From the collected fingerprints the feature vectors are extracted as a collection of different angle oriented features using the Gabor filter bank. The classes of the fingerprints are assigned as per the Henry System. For classification a novel FLANN-PSO algorithm is used and tested for accuracy through different parameters and different angular features of the fingerprints. In this work we have obtained an accuracy of 98% for real time collected fingerprint images. It has been compared with other classifiers and the results obtained of this work in terms of accuracy and MSE value has shown appreciable improvement over the other algorithms. pubtype: Academic Journal doctype: equations & formulas pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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