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Comprehensive Meaning Of Segmentation By Clustering |
by:
Eng.Mohamed S. El Kayyali |
Segmentation asword, means to classifyobjects that are exists inimage, it has many theories and methodologies, assume that we would like to recognize objects inimage, there are too many pixels to handle each individually, instead, we should like some form of compact, summary representation.
Although, superficially these different methods may seem some how complicated for any reader, in this article I will demonstratemeaning of clustering in segmentation.
One natural view of segmentation is that we are attempting to determine which components of data set naturally belong together. This isproblem known as clustering.
We can cluster in two ways:
-Partitioning: here we havelarge data set, and curve it up according to notion ofassociation between items insideset. We would like to decompose it into pieces that are good according to our model. For example we can decomposeimage into regions that have coherent color and texture.
-Grouping: in this part we have distinct data items, and we would like to collect sets of data items that make sense together.
The key here is to determine what representation is suitable forproblem at hand, we need to know by what criteriasegmentation method should decide which pixels belong together and which do not.
Once we decide which cluster method suitable for our application, segmentation by clustering could be very useful for some applications that may use clustering, as well as summarizing video, or finding machine parts, finding people in mage, finding buildings in satellite images: these done by looking for collections of edge points that can be assembled in line segment and then assembling line into polygons.
It is hard to see that there could becomprehensive theory of segmentation, not least what is interesting and what is not depends onapplication, there is no comprehensive theory of segmentation at time of writing.
Since clustering is defined above, in addition clustering isprocess wherebydata set is replaced by cluster, it is natural to think of segmentation as clustering, another meaning: pixels may belong together because they havesame color,same texture, they are nearby, and so on. Some of clustering methods as well as: clustering by K-means, segmentation by graph theoretic clustering.
Aboutauthor:
M.sc Eng. Mohamed S. El Kayyali - Resercher engineer at USMP and UTP medical image processing, founder of Kayyali edge detection theory. IEEE and CIPPRS member
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