Registration of microscopic iris image sequences using probabilistic mesh

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Abstract

This paper explores the use of deformable mesh for registration of microscopic iris image sequences. The registration, as an effort for stabilizing and rectifying images corrupted by motion artifacts, is a crucial step toward leukocyte tracking and motion characterization for the study of immune systems. The image sequences are characterized by locally nonlinear deformations, where an accurate analytical expression can not be derived through modeling of image formation. We generalize the existing deformable mesh and formulate it in a probabilistic framework, which allows us to conveniently introduce local image similarity measures, to model image dynamics and to maintain a well-defined mesh structure and smooth deformation through appropriate regularization. Experimental results demonstrate the effectiveness and accuracy of the algorithm. © Springer-Verlag Berlin Heidelberg 2006.

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APA

Song, X. B., Myronenko, A., Plank, S. R., & Rosenbaum, J. T. (2006). Registration of microscopic iris image sequences using probabilistic mesh. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4191 LNCS-II, pp. 553–560). Springer Verlag. https://doi.org/10.1007/11866763_68

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