Abstract
Segmentation of the iris is one of the key modules of an iris recognition system. For this reason, it is critical to predict failures of this module. In this article we propose a new set of segmentation quality metrics dedicated this problem. We assess the quality of our metrics based on their ability to predict the intrinsic recognition performance of a segmented image. A straightforward fusion procedure then allows generating a global segmentation quality score.
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Lefevre, T., Dorizzi, B., Garcia-Salicetti, S., Lemperiere, N., Belardi, S. (2013). Fusion of Novel Iris Segmentation Quality Metrics for Failure Detection. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2013. Lecture Notes in Computer Science, vol 7950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39094-4_12
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DOI: https://doi.org/10.1007/978-3-642-39094-4_12
Publisher Name: Springer, Berlin, Heidelberg
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