Successful conservation activities depend on reliable population information based on distribution, habitat use, or life history parameters of individual animals. To be able to assess whether a species is endangered, which conservational measures are most likely to be successful or whether these measures had the expected result, it is essential to have proper information on existing populations. The population information described above can only be gathered from many observations of individual animals during a period covering several years.

For recognition of individual animals, often tags attached to the animals are used. Tagging however, is invasive, costly and tags do not last a lifetime. It also induces stress and when a tag is lost (torn away) it may wound the animal. Photo-identification using natural marks such as spots and fin or tail shape is proven to be effective over the entire lifespan, it is relatively cheap and does not induce any stress or damage. The main disadvantage is that recognition of animals is based on manual inspection of the photo database. As more individuals are added to photo-identification databases with hundreds or even thousands of individuals, the manual matching process becomes extremely tedious and therefore loses accuracy. For many marine biologists the efficiency of their research is seriously obstructed by the absence of tools to assist the identification of individual animals from photos.

Automatic assistance in photo-identification takes away the only disadvantage of this superior technique compared with tagging. I³S is a free computer-aided photo-identification application that relies on natural marks to identify individual animals. I³S has proven very successful in identification of these species based on their natural spots. I³S helps the researcher to extract the spot pattern and then compares this pattern against all animals in the database and shows the researcher the most relevant results. When tested on a large whale shark database (~500 individuals, ~1600 images), I³S was able to recognize over 92% of recurring animals in the top 10 (2 reference images). Upon addition to the photo database, I³S expects the researcher to provide information about the spot pattern. This step takes about one to two minutes. After this step, the search is entirely automatic and highly accurate.

The name Interactive Individual Identification System explains most of I³S’ functionality. I³S is interactive and it is meant to support not to replace the researcher. Initially, the user has to point out the most distinguishing features (i.e. the spots and reference features, e.g. fins) of the unknown individual. In the next step, I³S assists the user in the tedious task of matching the (shark) image with a collection of images of known sharks. Results are shown as a ranked list. The user will always be responsible for making the final match between the unknown image and an image from the database.