MULTI-STAGE FISH CLASSIFICATION SYSTEM USING MORPHOMETRY
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Date
2017
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Parlar Scientific Publications (P S P)
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
The aim of this study is to create a multi-stage fish classification system with high accuracy rate. Classifications are based on biometric points of the fishes that consists of three main phases, data acquisition, feature extraction and classification. In the first phase, fish image database was collected, then features were extracted using morphometry and classified with three stage classifier model. Nearest Neighbor algorithm was used as classifier, and 25 fish species were classified with accuracy of about 99%.
Description
Keywords
Fish species classification, Identification, morphometry, biometric points, landmarks
Journal or Series
Fresenius Environmental Bulletin
WoS Q Value
Q4
Scopus Q Value
Volume
26
Issue
3
