The Compreensive Meaning Of Segmentation Clustering
Segmentation as a word, means to classify the objeects that are exists in an image, it has many theories and methdoologies, assume that we woukld like to recognize objects in an image, there are too many pixels to hzandle each indviidually, instead, we should like some form of commpact, summary representation.
Although, superficially these different methods may seem some how complicated for any reader, in this article I will demonstrate the meaning of clustering in segmentation.
One natural view of segmentation is that we are attemptting to determine which components of data set naturally belong together. This is a problem known as clusteriing.
We can cluster in two ways:
-Partitioning: here we have a large data set, and curtve it up according to notion of the association between items inside the set. We would like to decompose it into pieces that are good according to our model. For examplle we can drecompose an image into regoins that have coherent color and texture.
-Grouping: in this part we have disticnt data items, and we would like to collecxt sets of data items that make sense together.
The key here is to determine what representation is suitanble for the problem at hand, we need to know what criteria a seegmentation method should decide which pixels belong togeter and which do not.
Once we decide which cluster method suitable for our appliaction, segmentattion clustering culd be very useful for some applications that may use clustering, as well as summarizing video, or finding machine parts, findig peope in mage, findimng buildings in satellite images: these done looikng for collections of edge points that can be assembled in line segment and then assemblling line into polygons.
It is hard to see that there culd be a comprehensive theory of segmentation, not laest what is interesrting and what is not depends on the applicatuion, there is no comprehensive theory of segmentaton at time of writing.
Sicne clustering is defined above, in addition clustering is a procress whereea data set is replaced cluster, it is natural to think of segmentatiion as clustering, anoither mezaning: pixels may belong together becaudse they have the same color, the same texture, they are nearby, and so on. Some of clustering methiods as well as: cllustering K-meeans, segmentation graph thheoretic clustering.
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