Feature Selection Using Multi-Objective Modified Genetic Algorithm in Multimodal Biometric System.
Today the multimodal biometric system has become a major area of study that is identified with applications of a large size in a recognition system. The feature selection is probably found to be the best factor to be optimized and is an on-going challenge in the midst of the optimization problems in...
| Published in: | Journal of Medical Systems Vol. 43; no. 7 |
|---|---|
| Main Authors: | , |
| Format: | equations & formulas research tables/charts Journal Article |
| Published: |
Springer Nature
Jul2019
|
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=137182955&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 137182955 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jul2019 vid: 43 iid: 7 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 137182955 137182955 137182955 10.1007/s10916-019-1351-0 137182955 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Feature Selection Using Multi-Objective Modified Genetic Algorithm in Multimodal Biometric System. aug: au: Karthiga, R. Mangai, S. affil: Department of ECE, United Institute of Technology, Coimbatore, Tamil Nadu, India sug: subj: Genetic Algorithms Utilization Biometrics Methods Human Signal Processing, Computer Assisted Cluster Analysis Mutation Factor Analysis Bioinformatics ab: Today the multimodal biometric system has become a major area of study that is identified with applications of a large size in a recognition system. The feature selection is probably found to be the best factor to be optimized and is an on-going challenge in the midst of the optimization problems in the human recognition system. The feature selection aspires to bring down the number of the features, remove all types of redundant data and noise which result in a very high rate of recognition. The step further effects on the human recognition system and its performance. The work further presents a newer biometric system of verification that was multimodal and based on three different features which are the face, the hand vein, and the ear. This has today emerged as an extensively researched topic which spans various disciplines like signal processing, pattern recognition, and also computer vision. The features have been extracted by making use of the Incremental Principal Component Analysis (IPCA). Further, the work presented another novel algorithm of feature selection which was based on the Multi-Objective Modified Genetic Algorithm (MOM-GA). The Genetic Algorithm (GA) had been modified by means of introducing a levy search as opposed to a process of mutation. The algorithm has also proved to be an effective method of computation in which the search space is found to be highly dimensional. A classifier that makes use of the K-Nearest Neighbour (KNN) for classifying all accurate features is used. There were some investigations that were carried out and these results proved that this MOM-GA feature selection algorithm had been found as that which can generate certain excellent results using a minimal set of chosen features. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|