Identification of over One Thousand Individual Wild Humpback Whales using Fluke Photos

Identifying individual humpback whales by photographs of their tails is valuable for understanding the ecology of wild whales. We have about 10,000 photos of 1,850 identified whales taken in the sea area around Okinawa over a 30-year period. The identification process on this large scale of numbers is difficult not only for the human eye but also for machine vision, as the numbers of photographs per individual whale are very low. About 30% of the whales have only a single photograph, and 80% have fewer than five. In addition, the shapes of the tails and the black and white patterns on them are vague, and these change readily with the whale's slightest movement and changing photo-shooting conditions. We propose a practical method for identifying a humpback whale by accurate segmentation of the fluke region using a combination of deep neural networking and GrabCut. Then useful features for identifying each individual whale are extracted by both histograms of image features and wavelet transform of the trailing edge. The test results for 323 photos show the correct individuals are ranked within the top 30 for 89% of the photos, and at the same time for 76% of of photos ranked at the top.