Abstract
Image segmentation methods based on spectral graph theory, although capable of overcoming some of the drawbacks of the so-called “central”-grouping methods, are computationally expensive and quickly become infeasible to solve as the size of the image grows. As a counter measure, the Nyström approximation allows to extrapolate the complete grouping solution for these methods using only a proportionally smaller set of samples instead of the whole pixels that compose the image. In this correspondence, we further explore the Nyström approximation by taking the concept of “regions”, pixels of the image previously grouped by a central method, to both reduce the computational resources required and provide a finer segmentation of the image by combining the strengths of both methods. We apply the proposed approach to the segmentation of images of burns where we attempt to extract regions that would roughly correspond to the different degrees of the lesion.










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Acknowledgments
Salvador E. Venegas-Andraca would like to thank his family for their unconditional support. Also, he gratefully acknowledges the financial support of CONACyT (SNI member number 41594) and Tecnológico de Monterrey-Escuela de Ciencias e Ingeniería. Juan F. Garcia Garcia thankfully acknowledges the receipt of Grant 239454 from CONACyT. Both authors would like to thank Victor Alvaro Gutierrez Martinez and Luis Alberto Muñoz Ubando from Grupo Plenum, as well as Leonardo Bravo from Hospital Ruben Leñero for their support. Valuable feedback on an early version of this work was kindly provided by Walterio W. Mayol-Cuevas from the University of Bristol.
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García García, J.F., Venegas-Andraca, S.E. Region-based approach for the spectral clustering Nyström approximation with an application to burn depth assessment. Machine Vision and Applications 26, 353–368 (2015). https://doi.org/10.1007/s00138-015-0664-3
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DOI: https://doi.org/10.1007/s00138-015-0664-3