open access
Vol 77, No 2 (2018)
Review article
Submitted: 2017-06-30
Accepted: 2017-07-27
Published online: 2017-08-30
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How automated image analysis techniques help scientists in species identification and classification?
1, 2, 1
Affiliations- University of Malaya, Institute of Biological Sciences, Faculty of Science,, 50603 Kuala Lumpur, Malaysia
- University of Cambridge, Computer Laboratory 15 JJ Thomson Avenue Cambridge CB3 0FD, 01223 Cambridge, United Kingdom
open access
Vol 77, No 2 (2018)
REVIEW ARTICLES
Submitted: 2017-06-30
Accepted: 2017-07-27
Published online: 2017-08-30
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 articleTitle
How automated image analysis techniques help scientists in species identification and classification?
Journal
Issue
Article type
Review article
Pages
179-193
Published online
2017-08-30
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2174
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1977
DOI
Pubmed
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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