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Chapter 5

Segmentation

5.1 Active contours ................................. 237
5.1.1 Snakes ................................. 238
5.1.2 Dynamic snakes and CONDENSATION ................ 243
5.1.3 Scissors ................................. 246
5.1.4 Level Sets ................................ 248
5.1.5 Application: Contour tracking and rotoscoping ............ 249
5.2 Split and merge ................................. 250
5.2.1 Watershed ................................ 251
5.2.2 Region splitting (divisive clustering) .................. 251
5.2.3 Region merging (agglomerative clustering) .............. 251
5.2.4 Graph-based segmentation ....................... 252
5.2.5 Probabilistic aggregation ........................ 253
5.3 Mean shift and mode finding .......................... 254
5.3.1 K-means and mixtures of Gaussians .................. 256
5.3.2 Mean shift ............................... 257
5.4 Normalized cuts ................................. 260
5.5 Graph cuts and energy-based methods ..................... 264
5.5.1 Application: Medical image segmentation ............... 268
5.6 Additional reading ............................... 268
5.7 Exercises .................................... 270

R. Szeliski, Computer Vision: Algorithms and Applications, Texts in Computer Science, 235
DOI 10.1007/978-1-84882-935-0_5, © Springer-Verlag London Limited 2011