TY - GEN
T1 - Texture analysis for skin probability maps refinement
AU - Kawulok, Michal
PY - 2012
Y1 - 2012
N2 - In this paper a new method for skin regions detection and segmentation is proposed. To improve the conventional color-based skin models, skin probability maps are subject to texture analysis using discriminative statistical features. Although the texture was utilized for skin detection in some of the existing methods, the main contribution of the work reported here is that the probability maps rather than the original color images are processed. The method has been validated in a series of experiments using two data sets. The obtained results are reported in the paper, and they confirm that the method is competitive.
AB - In this paper a new method for skin regions detection and segmentation is proposed. To improve the conventional color-based skin models, skin probability maps are subject to texture analysis using discriminative statistical features. Although the texture was utilized for skin detection in some of the existing methods, the main contribution of the work reported here is that the probability maps rather than the original color images are processed. The method has been validated in a series of experiments using two data sets. The obtained results are reported in the paper, and they confirm that the method is competitive.
UR - https://www.scopus.com/pages/publications/84864194307
U2 - 10.1007/978-3-642-31149-9_8
DO - 10.1007/978-3-642-31149-9_8
M3 - Conference contribution
AN - SCOPUS:84864194307
SN - 9783642311482
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 75
EP - 84
BT - Pattern Recognition - 4th Mexican Conference, MCPR 2012, Proceedings
T2 - 4th Mexican Conference on Pattern Recognition, MCPR 2012
Y2 - 27 June 2012 through 30 June 2012
ER -