IS = { zkontrolovano 19 Aug 2009 },
  UPDATE  = { 2009-07-27 },
 author = {{\v C}ech, Jan and {\v S}{\'a}ra, Radim},
 title = {Languages for Constrained Binary Segmentation Based on 
          Maximum A Posteriori Probability Labeling},
 journal = {International Journal of Imaging Systems and Technology},
 issn = {0899-9457},
 volume = {19},
 number = {2},
 pages = {69-79},
 year = {2009},
 month = {June},
 DOI = {10.1002/ima.20181},
 publisher = {John Wiley & Sons, Inc.},
 address = {Hoboken, USA},
  ANNOTE = {We use a MRF with asymmetric pairwise compatibility
   constraints between direct pixel neighbors to solve a constrained
   binary image segmentation task. The model is constraining shape and
   alignment of individual contiguous binary segments by introducing
   auxiliary labels and their pairwise interactions. Such
   representation is not necessarily unique. We study several ad-hoc
   labeling models for binary images consisting of nonoverlapping
   rectangular contiguous regions.  Nesting and equivalence of these
   models are studied. We observed a noticeable increase in
   performance even in cases when the differences between the models
   were seemingly insignificant. We use the proposed models for
   segmentation of windowpanes and windows in orthographically
   rectified facade images. Segmented window patches are always
   axis-parallel nonoverlapping rectangles which must also be aligned
   in our strongest model. We show experimentally that even very weak
   data model in the MAP formulation of the optimal segmentation
   problem gives very good segmentation results.},
 keywords = {computer vision, image interpretation, 
             constrained segmentation, 2D image languages, MRF},
 project = {1ET101210406, FP6-IST-027113},
 authorship = {50-50},