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In this algorithm we scan through a grid looking for occupied cells and labelling them with cluster labels. The algorithm begins with scanning the grid cell by cell and check if the cell is occupied, if the cell is occupied then this cell must be labelled with a cluster label. This cluster label is decided based on the neighbors of the cell which have been previously scanned and labelled, and if the cell doesn’t have any occupied neighbors then new label is assigned to the cell.
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So in the raster scan of the grid in question, each time an occupied cell is encountered, a check is done to see whether this cell has any neighboring cells who have already been scanned. If so, first a '''''union''''' operation is performed, to specify that these neighboring cells are in fact members of the same equivalence class. Then a '''''find''''' operation is performed to find a representative member of that equivalence class with which to label the current cell. If, on the other hand, the current cell has no neighbors, it is assigned a new, previously unused, label. The entire grid is processed in this way. The grid can be raster-scanned a second time, performing only '''''find''''' operations at each cell, to re-label the cells with their final assignment of a representative element.
=== Raster Scan and Labelling on the
largest_label = 0;
for x in 0 to n_columns {
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== Applications ==
== More Clustering Algorithms ==
#BFR&(Bradley;Fayyad;Reina) algorithm
# k-means clustering algorithm
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