文件名称:segmentation
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This paper provides an algorithm for partitioning grayscale images into disjoint regions of coherent
brightness and texture. Natural images contain both textured and untextured regions, so the cues of contour and
texture differences are exploited simultaneously. Contours are treated in the intervening contour fr a mework, while
texture is analyzed using textons. Each of these cues has a domain of applicability, so to facilitate cue combination we
introduce a gating operator based on the texturedness of the neighborhood at a pixel. Having obtained a local measure
of how likely two nearby pixels are to belong to the same region, we use the spectral graph theoretic fr a mework of
normalized cuts to find partitions of the image into regions of coherent texture and brightness. Experimental results
on a wide range of images are shown.
brightness and texture. Natural images contain both textured and untextured regions, so the cues of contour and
texture differences are exploited simultaneously. Contours are treated in the intervening contour fr a mework, while
texture is analyzed using textons. Each of these cues has a domain of applicability, so to facilitate cue combination we
introduce a gating operator based on the texturedness of the neighborhood at a pixel. Having obtained a local measure
of how likely two nearby pixels are to belong to the same region, we use the spectral graph theoretic fr a mework of
normalized cuts to find partitions of the image into regions of coherent texture and brightness. Experimental results
on a wide range of images are shown.
相关搜索: normalized
cuts
and
image
segmentation
graph
cuts
texture
segmentation
region
based
segmentation
using
matlab
spectral
graph
local
graph
Graph
Theoretic
textons
range
image
texture
and
contour
cuts
and
image
segmentation
graph
cuts
texture
segmentation
region
based
segmentation
using
matlab
spectral
graph
local
graph
Graph
Theoretic
textons
range
image
texture
and
contour
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segmentation using eigenvector.pdf