These sharks boast a unique pattern of white spots on dark skin, which is similar to the kind of “blob extraction” that astrophysicists use to identify stars and other bodies in space.
Once it paved the way, this technology then opened the doors for other types of identification–this time, for dolphins. Through the use of manual photo identification, dolphins were able to be identified based on the marks on their dorsal fins. Yet even this process was too time consuming.
Recently, however, a computer science professor at Eckerd College has, along with the help of her students, created the program DARWIN (Digital Analysis and Recognition of Whale Images on a Network). This speeds up the process by using a combination of computer vision and signal processing techniques to make the process automated, as opposed to manual.
After creating an outline of the fin of a bottlenose dolphin, the system builds up a database and, using computer-vision algorithms, matches up identified fins in the database with those that are unknown. The images then are displayed in a ranking system, showing both matches that are highly probable, as well as those that aren’t as likely.
This is an interesting development for sea animals, because the identification process is faster and more reliable. But what practical applications might be involved? What benefits will researchers of marine life have from programs like this? And what applications can this have in other realms of computer vision and identification?