Polynomial-time solutions to image segmentation
Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms
Data structures for mobile data
Journal of Algorithms
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Deformable spanners and applications
Computational Geometry: Theory and Applications
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We propose a novel approach for solving the image segmentation and grouping problem. Our approach focuses on color and regional proximity relations in the image data. We treat image pixels as nodes in the graph so that proximity relations among both pixel's color and position are kept in geometric spanners. Geometric spanners for both color and position are created in hierarchical data structure so-called balls hierarchy. Balls hierarchy creates a multiresolution hierarchical subgraph that reflects a great deal about the original graph while maintaining all the existing proximity information in the image. We show that balls hierarchy can be used for image segmentation and grouping problems. We have applied our novel approach to several exemplary images such as histopathologic images and found results encouraging.