Abstract
Detailed data on individual animals are critical to ecological and evolutionary studies, but attaching identifying marks can alter individual fates and behavior leading to biases in parameter estimates and ethical issues. Individual-recognition software has been developed to assist in identifying many species from non-invasive photographic data. These programs utilize algorithms to find unique individual characteristics and compare images to a catalogue of known individuals. Currently, all applications for individual identification require manual processing to crop images so only the area of interest remains, or the area of interest must be manually delineated in each image. Thus, one of the main bottlenecks in processing data from photographic capture-recapture surveys is in cropping to an area of interest so that matching algorithms can identify the individual. Here, we describe the development and testing of an automated cropping program. The methods and techniques we describe are broadly applicable to any system where raw photos must be cropped down to a specific area of interest before pattern recognition software can be used for individual identification. We developed and tested the program for use with identification photos of wild giraffes.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 191-196 |
| Number of pages | 6 |
| Journal | Ecological Informatics |
| Volume | 50 |
| DOIs | |
| State | Published - Mar 1 2019 |
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All Science Journal Classification (ASJC) codes
- Ecology, Evolution, Behavior and Systematics
- Ecology
- Modeling and Simulation
- Ecological Modeling
- Computer Science Applications
- Computational Theory and Mathematics
- Applied Mathematics
Cite this
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An automated program to find animals and crop photographs for individual recognition. / Buehler, Patrick; Carroll, Bill; Bhatia, Ashish; Gupta, Vivek; Lee, Derek.
In: Ecological Informatics, Vol. 50, 01.03.2019, p. 191-196.Research output: Contribution to journal › Article
TY - JOUR
T1 - An automated program to find animals and crop photographs for individual recognition
AU - Buehler, Patrick
AU - Carroll, Bill
AU - Bhatia, Ashish
AU - Gupta, Vivek
AU - Lee, Derek
PY - 2019/3/1
Y1 - 2019/3/1
N2 - Detailed data on individual animals are critical to ecological and evolutionary studies, but attaching identifying marks can alter individual fates and behavior leading to biases in parameter estimates and ethical issues. Individual-recognition software has been developed to assist in identifying many species from non-invasive photographic data. These programs utilize algorithms to find unique individual characteristics and compare images to a catalogue of known individuals. Currently, all applications for individual identification require manual processing to crop images so only the area of interest remains, or the area of interest must be manually delineated in each image. Thus, one of the main bottlenecks in processing data from photographic capture-recapture surveys is in cropping to an area of interest so that matching algorithms can identify the individual. Here, we describe the development and testing of an automated cropping program. The methods and techniques we describe are broadly applicable to any system where raw photos must be cropped down to a specific area of interest before pattern recognition software can be used for individual identification. We developed and tested the program for use with identification photos of wild giraffes.
AB - Detailed data on individual animals are critical to ecological and evolutionary studies, but attaching identifying marks can alter individual fates and behavior leading to biases in parameter estimates and ethical issues. Individual-recognition software has been developed to assist in identifying many species from non-invasive photographic data. These programs utilize algorithms to find unique individual characteristics and compare images to a catalogue of known individuals. Currently, all applications for individual identification require manual processing to crop images so only the area of interest remains, or the area of interest must be manually delineated in each image. Thus, one of the main bottlenecks in processing data from photographic capture-recapture surveys is in cropping to an area of interest so that matching algorithms can identify the individual. Here, we describe the development and testing of an automated cropping program. The methods and techniques we describe are broadly applicable to any system where raw photos must be cropped down to a specific area of interest before pattern recognition software can be used for individual identification. We developed and tested the program for use with identification photos of wild giraffes.
UR - http://www.scopus.com/inward/record.url?scp=85061060614&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061060614&partnerID=8YFLogxK
U2 - 10.1016/j.ecoinf.2019.02.003
DO - 10.1016/j.ecoinf.2019.02.003
M3 - Article
AN - SCOPUS:85061060614
VL - 50
SP - 191
EP - 196
JO - Ecological Informatics
JF - Ecological Informatics
SN - 1574-9541
ER -