Indonesian Journal of Electrical Engineering and Computer Science
Vol 13, No 3: March 2015

Feature extraction and classification for multiple species of Gyrodactylus ectoparasite

Rozniza Ali (Universiti Malaysia Terengganu)
Amir Hussain (Stirling University)
Mustafa Man (Universiti Malaysia Terengganu)



Article Info

Publish Date
01 Mar 2015

Abstract

Active Shape Models (ASM) are applied to the attachment hooks of several species of Gyrodactylus, including the notifiable pathogen G. salaris, to assign each species to its truespecies type. Linear (i.e. LDA and K-NN) andnon-linear (i.e. MLP and SVM) models are used to classify Gyrodactylus species. Speciesof Gyrodactylus, ectoparasitic monogenetic flukes of fish, are difficult to discriminate andidentify according to morphology alone and their speciation currently requires taxonomicexpertise. The current exercise sets out to confidently classify species, which in this example includes a species which is a notifiable pathogen of Atlantic salmon, to their true classwith a high degree of accuracy. The findings from the current exercise demonstrates thatimport of ASM data into a MLP classifier, outperforms several other methods of classification (i.e. LDA, K-NN and SVM) that were assessed, with an average classification accuracyof 98.72%. DOI: http://dx.doi.org/10.11591/telkomnika.v13i3.7096

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