3.5 mins read
Leiwe & Partners helped a leading Caribbean marine research institute transition from an invasive sea turtle identification method to a cutting-edge AI-based biometric system, delivering a transformative ethical and operational shift.
Eliminated invasive tagging for the majority of turtle encounters
Restored field time previously lost to database searches
Improved data quality through automated detection of duplicate records and data-entry errors
Background
Located in the southern Caribbean, Bonaire is a critical nesting ground for endangered sea turtles, including green, loggerhead, hawksbill, and leatherback species.
For years, researchers relied on physically capturing, measuring, and applying a metal tag to the turtles' front flipper for identification. This process was fraught with issues:
Animal Welfare: The tagging process was invasive and time-consuming, increasing stress for the animal.
Data Integrity: Physical tags could fade or detach, leading to a high chance of duplicate data entries and incomplete time-series records.
Staff Overhead: When a tag was missing or questionable, staff had to painstakingly search a database of over 3,000 records, consuming a large part of the time that could be better spent on conservation work.
Challenge
Leiwe & Partners recognized that each sea turtle possesses a unique, unalterable pattern of scutes (facial scales). However, the photographs captured varied wildly—different cameras, lighting conditions, angles, and resolutions. The solution would need to handle real-world messiness, not laboratory perfection, especially since many photos were taken on boats in challenging field conditions.
Solution
Leveraging deep learning, the Leiwe team designed a three-stage recognition pipeline that transforms field photos into reliable identifications:
Stage 1: Finding the Face
The system automatically detects each turtle's head in the photo, removing distracting backgrounds. It then rotates the image to a standard orientation—essential when working with handheld camera shots.
Stage 2: Creating a Digital Fingerprint
Instead of storing thousands of full-resolution photos, the system extracts a unique "fingerprint" from each turtle's facial scale pattern. This approach keeps the system fast and lightweight, running smoothly even on modest hardware.
Stage 3: Intelligent Matching
When a new photo arrives, the system compares its fingerprint against the database. Initial matching achieved 69% accuracy, but Leiwe & Partners developed a custom confidence scoring method that analyzes the entire pattern of matches. This innovation boosted accuracy to 92% immediately and reached 100% after correcting four historical mislabeling errors in STCB's records.
Outcome
The transformation was dramatic. What once required hours of manual comparison now happens in minutes.
Beyond time savings, the system strengthens STCB's conservation mission. More accurate tracking means better understanding of migration patterns, population health, and individual turtle life histories—data that drives protection policies and donor funding.
By replacing invasive physical tags with non-invasive photo recognition, Leiwe & Partners delivered a more humane, scalable approach to protecting endangered species.
Looking Ahead:
Scaling Impact
The facial recognition solution is ready to scale. The next steps are creating a user-friendly application and expanding its reach to other endangered species monitoring programs.
The same facial recognition technology that works in your phone's photo library is now being deployed in the Caribbean, safeguarding sea turtles, one unique face at a time.