Keywords

Ursus maritimus, noninvasive, natural marking, photograph, reliability, computer-aided, information theory

Abstract

Many types of ecological studies require identification of individual animals. I developed and evaluated an automated identification system for polar bears (Ursus maritimus) based on their whisker spot patterns. First, I measured the reliability of using whisker spot patterns for identification from polar bear photographs taken in western Hudson Bay. This analysis involved estimating the complexity of each whisker spot pattern in terms of its information content. I found that 98% of patterns contained enough information to be reliable, and this result varied little among three different observers. Based on these results, I implemented a computer-aided identification system for polar bears based on whisker spot pattern recognition. I used standard computer vision techniques to pre-process images and the Chamfer distance transform to compute similary scores between images. In addition, I evaluated the system by testing the effects of photographic quality and angle on system accuracy. I found that excellent and moderate quality/angle provided best results, with system accuracy of 90-95%. These findings suggest that individual identification of polar bears in the field based on whisker spot pattern variation is possible. Researchers studying polar bear behavior or estimating population parameters should benefit from this noninvasive technique.

Notes

If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu

Graduation Date

2007

Semester

Spring

Advisor

Waterman, Jane

Degree

Master of Science (M.S.)

College

College of Sciences

Department

Biology

Degree Program

Biology

Format

application/pdf

Identifier

CFE0001671

URL

http://purl.fcla.edu/fcla/etd/CFE0001671

Language

English

Release Date

May 2007

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Included in

Biology Commons

Share

COinS