Description: This paper addresses the problem of segmenting an image into regions. We defi ne a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an effi cient segmentation algorithm based on this predicate, and show that although this algorithm makes greedy decisions it produces segmentations that satisfy global properties. We apply the al-gorithm to image segmentation using two diff erent kinds of local neighborhoods in constructing the graph, and illustrate the results with both real and synthetic images. The algorithm runs in time nearly linear in the number of graph edges and is also fast in practice. An important characteristic of the method is its ability to preserve detail in low-variability image regions while ignoring detail in high-variability regions.
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GraphSeg\license.txt
........\seg-ijcv.doc
........\seg-ijcv.pdf
........\GraphSeg\binaryHeap.h
........\........\GraphSeg.h
........\........\graphSeg.m
........\........\GraphSeg_mex.cpp
........\........\knng_search.m
........\........\license.txt
........\........\test_GraphSeg.m
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........\........\knng_search.asv
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........\........\coherenceFilter\CoherenceFilter.m
........\........\...............\compile_c_files.m
........\........\...............\license.txt
........\........\...............\functions\derivatives.c
........\........\...............\.........\derivatives.m
........\........\...............\.........\imgaussian.c
........\........\...............\.........\imgaussian.m
........\........\...............\.........\showcs3.fig
........\........\...............\.........\showcs3.m
........\........\...............\.........2D\CoherenceFilterStep2D.c
........\........\...............\...........\CoherenceFilterStep2D.m
........\........\...............\...........\CoherenceFilterStep2D_functions.c
........\........\...............\...........\ConstructDiffusionTensor2D.m
........\........\...............\...........\diffusion_scheme_2D_implicit.m
........\........\...............\...........\diffusion_scheme_2D_non_negativity.m
........\........\...............\...........\diffusion_scheme_2D_rotation_invariant.m
........\........\...............\...........\diffusion_scheme_2D_standard.m
........\........\...............\...........\EigenVectors2D.m
........\........\...............\...........\StructureTensor2D.m
........\........\...............\.........3D\CoherenceFilterStep3D.c
........\........\...............\...........\CoherenceFilterStep3D.m
........\........\...............\...........\CoherenceFilterStep3D_functions.c
........\........\...............\...........\diffusion_scheme_3D_implicit.m
........\........\...............\...........\diffusion_scheme_3D_non_negativity.c
........\........\...............\...........\diffusion_scheme_3D_non_negativity.m
........\........\...............\...........\diffusion_scheme_3D_rotation_invariant.c
........\........\...............\...........\diffusion_scheme_3D_rotation_invariant.m
........\........\...............\...........\diffusion_scheme_3D_standard.c
........\........\...............\...........\diffusion_scheme_3D_standard.m
........\........\...............\...........\EigenDecomposition3.c
........\........\...............\...........\EigenDecomposition3.h
........\........\...............\...........\EigenVectors3D.c
........\........\...............\...........\EigenVectors3D.m
........\........\...............\...........\StructureTensor2DiffusionTensor3DWeickert.c
........\........\...............\...........\StructureTensor2DiffusionTensor3DWeickert.m
........\........\...............\...........\StructureTensor3D.m
........\........\...............\images\sphere.mat
........\........\...............\......\sync.png
........\........\...............\......\sync_noise.png
........\........\GLtree3DMex\BuildGLTree.cpp
........\........\...........\BuildGLTree.m
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