Abstract
Tree log biometrics is an approach to establish log traceability from forest to further processing companies. This work assesses if algorithms developed in the context of fingerprint and iris recognition can be transferred to log identification by means of cross-section images of log ends. Based on a test set built up on 155 tree logs the identification performances for a set of configurations and in addition the impacts of two enhancement procedures are assessed.
Results show, that fingerprint and iris recognition based approaches are suited for log identification by achieving 100% detection rate for the best configurations. In assessing the performance for a large set of tree logs this work provides substantial conclusions for the further development of log biometrics.
This work is partially funded by the Austrian Science Fund (FWF) under Project No. TRP-254.
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Schraml, R., Hofbauer, H., Petutschnigg, A., Uhl, A. (2015). Tree Log Identification Based on Digital Cross-Section Images of Log Ends Using Fingerprint and Iris Recognition Methods. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9256. Springer, Cham. https://doi.org/10.1007/978-3-319-23192-1_63
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DOI: https://doi.org/10.1007/978-3-319-23192-1_63
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