open access

Vol 77, No 2 (2018)
REVIEW ARTICLES
Published online: 2017-08-30
Submitted: 2017-06-30
Accepted: 2017-07-27
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How automated image analysis techniques help scientists in species identification and classification?

E. Yousef Kalafi, C. Town, S. Kaur Dhillon
DOI: 10.5603/FM.a2017.0079
·
Pubmed: 28868609
·
Folia Morphol 2018;77(2):179-193.

open access

Vol 77, No 2 (2018)
REVIEW ARTICLES
Published online: 2017-08-30
Submitted: 2017-06-30
Accepted: 2017-07-27

Abstract

Identification of taxonomy at a specific level is time consuming and reliant upon expert ecologists. Hence the demand for automated species identification incre­ased over the last two decades. Automation of data classification is primarily focussed on images while incorporating and analysing image data has recently become easier due to developments in computational technology. Research ef­forts on identification of species include specimens’ image processing, extraction of identical features, followed by classifying them into correct categories. In this paper, we discuss recent automated species identification systems, mainly for categorising and evaluating their methods. We reviewed and compared different methods in step by step scheme of automated identification and classification systems of species images. The selection of methods is influenced by many variables such as level of classification, number of training data and complexity of images. The aim of writing this paper is to provide researchers and scientists an extensive background study on work related to automated species identification, focusing on pattern recognition techniques in building such systems for biodiversity studies. (Folia Morphol 2018; 77, 2: 179–193)

Abstract

Identification of taxonomy at a specific level is time consuming and reliant upon expert ecologists. Hence the demand for automated species identification incre­ased over the last two decades. Automation of data classification is primarily focussed on images while incorporating and analysing image data has recently become easier due to developments in computational technology. Research ef­forts on identification of species include specimens’ image processing, extraction of identical features, followed by classifying them into correct categories. In this paper, we discuss recent automated species identification systems, mainly for categorising and evaluating their methods. We reviewed and compared different methods in step by step scheme of automated identification and classification systems of species images. The selection of methods is influenced by many variables such as level of classification, number of training data and complexity of images. The aim of writing this paper is to provide researchers and scientists an extensive background study on work related to automated species identification, focusing on pattern recognition techniques in building such systems for biodiversity studies. (Folia Morphol 2018; 77, 2: 179–193)

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Keywords

automated image recognition, digital image processing, species images, species classification, life data technology

About this article
Title

How automated image analysis techniques help scientists in species identification and classification?

Journal

Folia Morphologica

Issue

Vol 77, No 2 (2018)

Pages

179-193

Published online

2017-08-30

DOI

10.5603/FM.a2017.0079

Pubmed

28868609

Bibliographic record

Folia Morphol 2018;77(2):179-193.

Keywords

automated image recognition
digital image processing
species images
species classification
life data technology

Authors

E. Yousef Kalafi
C. Town
S. Kaur Dhillon

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