|Author(s)||Patrick Buehler, Bill Carroll, Ashish Bhatia, Vivek Gupta and Derek E. Lee|
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.
Keywords: Animal detection, Capture-recapture, Computer vision, Histogram of oriented gradients, Image processing, Individual identification, Photo identification
Authors: Patrick Buehler, Bill Carroll, Ashish Bhatia, Vivek Gupta and Derek E. Lee
Journal: Ecological Informatics