文件名称:Imasas
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Image segmentation is among the most studied problems in image understanding and
computer vision. The goal of image segmentation is to partition the image plane into
a set of meaningful regions. Here meaningful typically refers to a semantic partitioning
where the computed regions correspond to individual objects in the observed scene.
Unfortunately, generic purely low-level segmentation algorithms often do not provide the
desired segmentation results, because the traditional low level assumptions like intensity
or texture homogeneity and strong edge contrast are not sufficient to separate objects in a
scene.
computer vision. The goal of image segmentation is to partition the image plane into
a set of meaningful regions. Here meaningful typically refers to a semantic partitioning
where the computed regions correspond to individual objects in the observed scene.
Unfortunately, generic purely low-level segmentation algorithms often do not provide the
desired segmentation results, because the traditional low level assumptions like intensity
or texture homogeneity and strong edge contrast are not sufficient to separate objects in a
scene.
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978-0-387-92920-0_33.pdf
978-3-642-25085-9_14.pdf