Image segmentation: Difference between revisions

Revision as of 19:57, 12 June 2005

Revision as of 07:37, 25 June 2005

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{{technical}}

In [[image analysis]], '''segmentation''' is the [[partition]] of a [[digital image]] into multiple regions ([[set]]s of [[pixel]]s), according to some criterion.

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Segmentation criteria can be arbitrarily complex, and take into account global as well as local criteria. A common requirement is that each region must be [[connected]] in some sense.

An example of a global segmentation criteriacriterion is the famous [[Mumford-Shah]] functional. This functional measures the degree of matchmatching between an image and its segmentation. A segmentation consists of a set of non-overlapping connected regions (the union of which is the image ___domain), each of which is smooth and each of which has a piece-wisepiecewise smooth boundary. The functional penalizes deviations from the original image, deviations from smoothness within in each region and the total length of the boundaries of all the regions. Mathematically,

<math>

E \left( f,\Gamma \right) ={\mu}^{2}\int \!\!\!\int_{R} \! \left( f-g

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[[Category:Image processing]]

{{wikicities|computervision|Computer Vision}}

[[de:Segmentierung (Bildbearbeitung)]]
[[fr:Segmentation d'image]]