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The identification of mammalian species through the classification of hair patterns using image pattern recognition

Moyo, Thamsanqa, Bangay, Shaun and Foster, Greg 2006, The identification of mammalian species through the classification of hair patterns using image pattern recognition, in Afrigraph '06 : Proceedings of the 4th international conference on computer graphics, virtual reality, visualisation and interaction in Africa, Association for Computer Machinery, New York, N.Y., pp. 177-181, doi: 10.1145/1108590.1108619.

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Title The identification of mammalian species through the classification of hair patterns using image pattern recognition
Author(s) Moyo, Thamsanqa
Bangay, Shaun
Foster, Greg
Conference name International conference on computer graphics, virtual reality, visualisation and interaction in Africa (4th : 2006 : Cape Town, South Africa)
Conference location Cape Town, South Africa
Conference dates 25-27 Jan. 2006
Title of proceedings Afrigraph '06 : Proceedings of the 4th international conference on computer graphics, virtual reality, visualisation and interaction in Africa
Editor(s) Spencer, Stephen N.
Publication date 2006
Conference series International Conference on Computer Graphics, Virtual Reality, Visualisation and Interaction in Africa
Start page 177
End page 181
Publisher Association for Computer Machinery
Place of publication New York, N.Y.
Summary The identification of mammals through the use of their hair is important in the fields of forensics and ecology. The application of computer pattern recognition techniques to this process provides a means of reducing the subjectivity found in the process, as manual techniques rely on the interpretation of a human expert rather than quantitative measures. The first application of image pattern recognition techniques to the classification of African mammalian species using hair patterns is presented. This application uses a 2D Gabor filter-bank and motivates the use of moments to classify hair scale patterns. Application of a 2D Gabor filter-bank to hair scale processing provides results of 52% accuracy when using a filter bank of size four and 72% accuracy when using a filter-bank of size eight. These initial results indicate that 2D Gabor filters produce information that may be successfully
ISBN 1595932887
Language eng
DOI 10.1145/1108590.1108619
Field of Research 080106 Image Processing
Socio Economic Objective 890299 Computer Software and Services not elsewhere classified
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2006, ACM
Persistent URL http://hdl.handle.net/10536/DRO/DU:30039191

Document type: Conference Paper
Collection: School of Information Technology
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