AUTOMATIC TATTOO RECOGNITION: APPLICATION IN THE FORENSIC FIELD
DOI:
https://doi.org/10.56238/revgeov16n5-044Keywords:
SIFT, YOLO, SURF, Tattoo, RecognitionAbstract
This work presents a system for the automatic recognition of tattoo images within a database, which can be used to assist in the accurate identification of criminals who bear such body marks, their meanings, and the possible identification of criminal factions to which they may belong. The techniques for parameter extraction and image recognition are based on the Scale Invariant Feature Transform (SIFT) algorithm, the Speeded-Up Robust Features (SURF) algorithm, and the YOLO neural network. The study describes the test cases that must be followed, which will allow for consistent performance comparison of tattoo recognition methods. The results showed good performance of the SIFT algorithm (88.65%) compared to the other methods analyzed.
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