Part of monograph

Haindl M., Mikeš S.

Yin P. ,

Pattern Recognition

Unsupervised Texture Segmentation, chapter 9

I-Tech Education and Publishing

Vienna

2008

978-953-7619-24-4

prof. Ing. Michal Haindl, DrSc. (ÚTIA - Oddělení rozpoznávání obrazů)

texture segmentation, image segmentation, unsupervised segme

Segmentation is the fundamental process which partitions a data space into meaningful salient regions. Image segmentation essentially affects the overall performance of any automated image analysis system thus its quality is of the utmost importance. Image regions, homogeneous with respect to some usually textural or colour measure, which result from a segmentation algorithm are analysed in subsequent interpretation steps. Several new unsupervised multispectral texture segmentation methods based on underlying Markovian spatial models with unknown number of classes are presented in the chapter. The performances of the presented methods are extensively tested on the Prague segmentation benchmark using the commonest segmentation criteria and compares favourably with several alternative texture segmentation methods.