Publication Type:

Conference Paper


Medical Imaging, International Society for Optics and Photonics (2007)


<p>We propose Compressed Connected Components (CxCxC), a new fast algorithm for labeling connected components in binary images making use of compression. We break the given 3D image into non-overlapping 2x2x2 cube of voxels (2x2 square of pixels for 2D) and encode these binary values as the bits of a single decimal integer. We perform the connected component labeling on the resulting compressed data set. A recursive labeling approach by the use of smart-masks on the encoded decimal values is performed. The output is finally decompressed back to the original size by decimal-to-binary conversion of the cubes to retrieve the connected components in a lossless fashion. We demonstrate the efficacy of such encoding and labeling for large data sets (up to 1392 x 1040 for 2D and 512 x 512 x 336 for 3D). CxCxC reports a speed gain of 4x for 2D and 12x for 3D with memory savings of 75% for 2D and 88% for 3D over conventional (recursive growing of component labels) connected components algorithm. We also compare our method with those of VTK and ITK and find that we outperform both with speed gains of 3x and 6x for 3D. These features make CxCxC highly suitable for medical imaging and multi-media applications where the size of data sets and the number of connected components can be very large.</p>

Cite this Research Publication

N. Nagaraj and Dwivedi, S., “CxCxC: Compressed Connected Components Labeling Algorithm”, in Medical Imaging, 2007.