Visual identification of individual animals that bear unique natural body markings is an important task in wildlife conservation. The photo databases of animal markings grow larger and each new observation has to be matched against thousands of images. Existing photo-identification solutions have constraints on image quality and appearance of the pattern of interest in the image. These constraints limit the use of photos from citizen scientists. We present a novel system for visual re-identification based on unique natural markings that is robust to occlusions, viewpoint and illumination changes. We adapt methods developed for face re-identification and implement a deep convolutional neural network (CNN) to learn embeddings for images of natural markings. The distance between the learned embedding points provides a dissimilarity measure between the corresponding input images. The network is optimized using the triplet loss function and the online semi-hard triplet mining strategy. The proposed re-identification method is generic and not species specific. We evaluate the proposed system on image databases of manta ray belly patterns and humpback whale flukes. To be of practical value and adopted by marine biologists, a re-identification system needs to have a top-10 accuracy of at least 95 . The proposed system achieves this performance standard.
Abstract Photo-identification using animals' natural markings is a cheaper and less impactful alternative to the use of more conventional external or internal tags for identifying individual animals. Photo-ID has already been successfully employed to monitor hard-shelled sea turtles, specifically using facial scales. However, photographing facial features might cause stress on photosensitive sea turtles, especially at night. Considering that there are more scales on the flippers than on the face and flipper photography is likely to be less invasive, we proposed an alternative method for photo-identification using the scale patterns on the front flippers. This method might also be suitable for successful photo-identification of hatchlings – which has been ineffectual using facial scales. To test the suitability of using the front flippers for photo-ID sea turtles, we took photos of the right flippers of adult and hatchling green turtles (Chelonia mydas) and olive ridley turtles (Lepidochelys olivacea) from Cabuyal, Costa Rica. The photos were analysed using APHIS, which delimits an area of interest with three reference points and then uses several additional points within this area to mark the intersections between scales. In both species, hatchlings and adults were correctly identified 92.9 and 81.8 of the time respectively but the capability of APHIS to correctly identify individuals was highly dependent on the quality of the photo. We detected similarities in flipper scale pattern between hatchlings of the same species but not between hatchlings from the same nest, indicating that hatchlings have unique flipper markings. The use of flipper scale patterns to identify individual sea turtles is comparable to the use of facial scales, without the risk of disturbing nesting females. Additionally, we were able to reliably identify individual hatchlings, which has not been possible using facial scales or conventional tagging techniques. Flipper scale patterns may potentially be a new methodology for identifying hatchlings both short- and long-term. We discuss the benefits and limitations of using sea turtle flipper scale patterns for identification as well as the benefits and limitation of APHIS. Summary 1 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. 2 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. 3 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. 4 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. Abstract Photographic identification methods are of highly importance when it comes to reduce the animal's stress, pain and possible injuries during or after marking techniques and thus to increase the reliability of demographic parameter estimates. There is plenty of software available for photo-identification, allowing individual identification in capture-mark-recapture (CMR) methods using body patterns, spots and marks unique to each individual. However, these non-invasive methods have hardly ever been used with arthropods. In this study, APHIS (Automated PHoto Identification Suite) has been assessed as a software capable of identifying individuals in different samplings during catch-and-release sessions with dead specimens under laboratory conditions. For this individual identification, SPM (Spot Pattern Matching) and ITM (Image Template Matching) procedures were tested; achieving a success of 100 and 95.35 , respectively. In SPM, the software itself matched the specimens almost automatically in half of the cases. However, it resulted more time-consuming than ITM during the pre-processing of images. On the other hand, ITM saves time during this step and still is able to detect recaptures accurately, yet more time may be needed when selecting the recaptures from the candidate list. Thus, it can be attested that APHIS is a competent and efficient software regarding photo-identification of Rhynchophorus ferrugineus and species with similar and unique individual colour patterns in their pronotum. Abstract Unique body characteristics are increasingly used for individual recognition to avoid the effort and the potential negative effects of capture–mark–recapture technique. As a consequence there is a growing demand for computer procedures to assist users in photo-recognition of an individual. We present a new software for photo-matching developed to minimize the pre-processing time and maximize the speed of the matching procedure. In APHIS photos can be processed in batches of hundreds and users can select between two alternative matching procedures, one interactive, built as an extension of existing and freely available software, and one automatic. We assessed its performance in terms of individual recognition and time efficiency and illustrate its use with real capture-photo–recapture studies on a reptile and an amphibian species, the Balearic Lizard Podiarcis lilfordi and the Northern spectacled salamander Salamandrina perspicillata , with contrasting skin patterns.