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

Abstract

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 used to classify hair according to images of its patterns.