A computer-aided program for pattern-matching of natural marks on the spotted raggedtooth shark Carcharias taurus

The ability to identify individual animals is a critical aid in wildlife and conservation studies requiring information on behaviour, distribution, habitat use, population and life-history parameters. We present a computer-aided photo-identification technique that relies on natural marks to identify individuals of Carcharias taurus, a shark species that is critically endangered off the eastern Australian coast and considered globally vulnerable. The technique could potentially be applied to a range of species of similar form and bearing natural marks. The use of natural marks for photo-identification is a non-invasive technique for identifying individual animals. As photo-identification databases grow larger, and their implementation spans several years, the historically used visual-matching processes lose accuracy and speed. A computerized pattern-matching system that requires initial user interaction to select the key features aids researchers by considerably reducing the time needed for identification of individuals. Our method uses a two-dimensional affine transformation to compare two individuals in a commonly defined reference space. The methodology was developed using a database of 221 individually identifiable sharks that were photographically marked and rephotographed over 9 years, demonstrating both the efficacy of the technique and that the natural pigment marks of C. taurus are a reliable means of tracking individuals over several years. Synthesis and applications. The identification of individual animals that are naturally marked with spots or similar patterns is achieved with an interactive pattern-matching system that uses an affine transformation to compare selected points in a single-user computer-aided interface. Our technique has been used successfully on C. taurus and we believe the methodology can be applied to other species of a similar form that have natural marks or patterns. The identification of individuals allows accurate tracking of their movements and distribution, and contributes to better population estimates for improved wildlife management and conservation planning.