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Referring to MATLAB, the basic steps are

Determine the connected components:

CC = bwconncomp(BW, conn);

Compute the area of each component:

S = regionprops(CC, 'Area');

Remove small objects:

L = labelmatrix(CC); BW2 = ismember(L, find([S.Area] >= P));

At the last step, after obtaining L$L$, you might as well retain the component with the largest area if you are interested in a single component. This would make the algorithm invariant to the size of the noise.

Referring to MATLAB, the basic steps are

Determine the connected components:

CC = bwconncomp(BW, conn);

Compute the area of each component:

S = regionprops(CC, 'Area');

Remove small objects:

L = labelmatrix(CC); BW2 = ismember(L, find([S.Area] >= P));

At the last step, after obtaining L, you might as well retain the component with the largest area if you are interested in a single component. This would make the algorithm invariant to the size of the noise.

Referring to MATLAB, the basic steps are

Determine the connected components:

CC = bwconncomp(BW, conn);

Compute the area of each component:

S = regionprops(CC, 'Area');

Remove small objects:

L = labelmatrix(CC); BW2 = ismember(L, find([S.Area] >= P));

At the last step, after obtaining $L$, you might as well retain the component with the largest area if you are interested in a single component. This would make the algorithm invariant to the size of the noise.

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source | link

Referring to MATLAB, the basic steps are

Determine the connected components:

CC = bwconncomp(BW, conn);

Compute the area of each component:

S = regionprops(CC, 'Area');

Remove small objects:

L = labelmatrix(CC); BW2 = ismember(L, find([S.Area] >= P));

At the last step, after obtaining L, you might as well retain the component with the largest area if you are interested in a single component. This would make the algorithm invariant to the size of the noise.