Assessing the performance of open-source, semi-automated pattern recognition software for harbour seal (P. v. vitulina) photo ID
Funding: Data collection was funded by the Scottish Government (grant number MMSS/002/15) Photographic identification (photo ID) is a well-established, non-invasive, and relatively cost-effective technique to collect longitudinal data from species that can be individually recognised based on natural...
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Online Access: | http://hdl.handle.net/10023/26586 https://doi.org/10.1007/s42991-021-00165-8 |
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ftstandrewserep:oai:research-repository.st-andrews.ac.uk:10023/26586 2023-07-02T03:32:30+02:00 Assessing the performance of open-source, semi-automated pattern recognition software for harbour seal (P. v. vitulina) photo ID Langley, Izzy Hague, Emily Arso Civil, Monica University of St Andrews. School of Biology University of St Andrews. Sea Mammal Research Unit 2022-12-14 10 application/pdf http://hdl.handle.net/10023/26586 https://doi.org/10.1007/s42991-021-00165-8 eng eng Mammalian Biology Langley , I , Hague , E & Arso Civil , M 2022 , ' Assessing the performance of open-source, semi-automated pattern recognition software for harbour seal ( P. v. vitulina ) photo ID ' , Mammalian Biology , vol. 102 , pp. 973-982 . https://doi.org/10.1007/s42991-021-00165-8 1616-5047 PURE: 277085347 PURE UUID: 19c45c3b-fe54-4938-b754-c3572cf649ad ORCID: /0000-0001-8239-9526/work/105007001 Scopus: 85120699225 WOS: 000730033300002 ORCID: /0000-0002-8957-1373/work/116598371 http://hdl.handle.net/10023/26586 https://doi.org/10.1007/s42991-021-00165-8 Copyright © 2021 Deutsche Gesellschaft für Säugetierkunde. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1007/s42991-021-00165-8. Pattern recognition Photo ID Software comparison Harbour seal Phoca vitulina vitulina Wild-ID GC Oceanography QA76 Computer software QL Zoology NDAS AC MCC GC QA76 QL Journal article 2022 ftstandrewserep https://doi.org/10.1007/s42991-021-00165-8 2023-06-13T18:26:10Z Funding: Data collection was funded by the Scottish Government (grant number MMSS/002/15) Photographic identification (photo ID) is a well-established, non-invasive, and relatively cost-effective technique to collect longitudinal data from species that can be individually recognised based on natural markings. This method has been improved by computer-assisted pattern recognition software which speed up the processing of large numbers of images. Freely available algorithms exist for a wide range of species, but the choice of software can have significant effects on the accuracy of individual capture histories and derived demographic parameter estimates. We tested the performance of three open source, semi-automated pattern recognition software algorithms for harbour seal (Phoca vitulina vitulina) photo ID: ExtractCompare, I3S Pattern and Wild-ID. Performance was measured as the ability of the software to successfully score matching images higher than non-matching images using the cumulative density function (CDF). The CDF for the top ranked potential match was highest for Wild-ID (CDF1 = 0.34–0.58), followed by ExtractCompare (CDF1 = 0.24–0.36) and I3S pattern (CDF1 = 0.02–0.3). This trend emerged regardless of how many potential matches were inspected. The highest performing aspects in ExtractCompare were left heads, whereas in I3S Pattern and Wild-ID these were front heads. Within each aspect, images collected using a camera and lens performed higher than images taken by a camera and scope. Data processing within ExtractCompare took > 4 × longer than Wild-ID, and > 3 × longer than I3S Pattern. We found that overall, Wild-ID outperformed both ExtractCompare and I3S Pattern under tested scenarios, and we therefore recommend its assistance in harbour seal photo ID. Postprint Peer reviewed Article in Journal/Newspaper harbour seal Phoca vitulina University of St Andrews: Digital Research Repository Mammalian Biology 102 3 973 982 |
institution |
Open Polar |
collection |
University of St Andrews: Digital Research Repository |
op_collection_id |
ftstandrewserep |
language |
English |
topic |
Pattern recognition Photo ID Software comparison Harbour seal Phoca vitulina vitulina Wild-ID GC Oceanography QA76 Computer software QL Zoology NDAS AC MCC GC QA76 QL |
spellingShingle |
Pattern recognition Photo ID Software comparison Harbour seal Phoca vitulina vitulina Wild-ID GC Oceanography QA76 Computer software QL Zoology NDAS AC MCC GC QA76 QL Langley, Izzy Hague, Emily Arso Civil, Monica Assessing the performance of open-source, semi-automated pattern recognition software for harbour seal (P. v. vitulina) photo ID |
topic_facet |
Pattern recognition Photo ID Software comparison Harbour seal Phoca vitulina vitulina Wild-ID GC Oceanography QA76 Computer software QL Zoology NDAS AC MCC GC QA76 QL |
description |
Funding: Data collection was funded by the Scottish Government (grant number MMSS/002/15) Photographic identification (photo ID) is a well-established, non-invasive, and relatively cost-effective technique to collect longitudinal data from species that can be individually recognised based on natural markings. This method has been improved by computer-assisted pattern recognition software which speed up the processing of large numbers of images. Freely available algorithms exist for a wide range of species, but the choice of software can have significant effects on the accuracy of individual capture histories and derived demographic parameter estimates. We tested the performance of three open source, semi-automated pattern recognition software algorithms for harbour seal (Phoca vitulina vitulina) photo ID: ExtractCompare, I3S Pattern and Wild-ID. Performance was measured as the ability of the software to successfully score matching images higher than non-matching images using the cumulative density function (CDF). The CDF for the top ranked potential match was highest for Wild-ID (CDF1 = 0.34–0.58), followed by ExtractCompare (CDF1 = 0.24–0.36) and I3S pattern (CDF1 = 0.02–0.3). This trend emerged regardless of how many potential matches were inspected. The highest performing aspects in ExtractCompare were left heads, whereas in I3S Pattern and Wild-ID these were front heads. Within each aspect, images collected using a camera and lens performed higher than images taken by a camera and scope. Data processing within ExtractCompare took > 4 × longer than Wild-ID, and > 3 × longer than I3S Pattern. We found that overall, Wild-ID outperformed both ExtractCompare and I3S Pattern under tested scenarios, and we therefore recommend its assistance in harbour seal photo ID. Postprint Peer reviewed |
author2 |
University of St Andrews. School of Biology University of St Andrews. Sea Mammal Research Unit |
format |
Article in Journal/Newspaper |
author |
Langley, Izzy Hague, Emily Arso Civil, Monica |
author_facet |
Langley, Izzy Hague, Emily Arso Civil, Monica |
author_sort |
Langley, Izzy |
title |
Assessing the performance of open-source, semi-automated pattern recognition software for harbour seal (P. v. vitulina) photo ID |
title_short |
Assessing the performance of open-source, semi-automated pattern recognition software for harbour seal (P. v. vitulina) photo ID |
title_full |
Assessing the performance of open-source, semi-automated pattern recognition software for harbour seal (P. v. vitulina) photo ID |
title_fullStr |
Assessing the performance of open-source, semi-automated pattern recognition software for harbour seal (P. v. vitulina) photo ID |
title_full_unstemmed |
Assessing the performance of open-source, semi-automated pattern recognition software for harbour seal (P. v. vitulina) photo ID |
title_sort |
assessing the performance of open-source, semi-automated pattern recognition software for harbour seal (p. v. vitulina) photo id |
publishDate |
2022 |
url |
http://hdl.handle.net/10023/26586 https://doi.org/10.1007/s42991-021-00165-8 |
genre |
harbour seal Phoca vitulina |
genre_facet |
harbour seal Phoca vitulina |
op_relation |
Mammalian Biology Langley , I , Hague , E & Arso Civil , M 2022 , ' Assessing the performance of open-source, semi-automated pattern recognition software for harbour seal ( P. v. vitulina ) photo ID ' , Mammalian Biology , vol. 102 , pp. 973-982 . https://doi.org/10.1007/s42991-021-00165-8 1616-5047 PURE: 277085347 PURE UUID: 19c45c3b-fe54-4938-b754-c3572cf649ad ORCID: /0000-0001-8239-9526/work/105007001 Scopus: 85120699225 WOS: 000730033300002 ORCID: /0000-0002-8957-1373/work/116598371 http://hdl.handle.net/10023/26586 https://doi.org/10.1007/s42991-021-00165-8 |
op_rights |
Copyright © 2021 Deutsche Gesellschaft für Säugetierkunde. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1007/s42991-021-00165-8. |
op_doi |
https://doi.org/10.1007/s42991-021-00165-8 |
container_title |
Mammalian Biology |
container_volume |
102 |
container_issue |
3 |
container_start_page |
973 |
op_container_end_page |
982 |
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