Grouping and segmentation of images remains a challenging problem in computer vision. Recently, a number of authors have demonstrated a good performance on this task using spectral methods that are based on the eigensolution of a similarity matrix. In this paper, we implement a variation of the existing methods that combines aspects from several of the best-known eigenvector segmentation algorithms to produce a discrete optimal solution of the relaxed continuous eigensolution. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Monteiro, F. C., & Campilho, A. C. (2005). Spectral methods in image segmentation: A combined approach. In Lecture Notes in Computer Science (Vol. 3523, pp. 191–198). Springer Verlag. https://doi.org/10.1007/11492542_24
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