TY - GEN
T1 - Bagging stochastic watershed on natural color image segmentation
AU - Franchi, Gianni
AU - Angulo, Jesús
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - The stochastic watershed is a probabilistic segmentation approach which estimates the probability density of contours of the image from a given gradient. In complex images, the stochastic watershed can enhance insignificant contours. To partially address this drawback, we introduce here a fully unsupervised multi-scale approach including bagging. Re-sampling and bagging is a classical stochastic approach to improve the estimation. We have assessed the performance, and compared to other version of stochastic watershed, using the Berkeley segmentation database.
AB - The stochastic watershed is a probabilistic segmentation approach which estimates the probability density of contours of the image from a given gradient. In complex images, the stochastic watershed can enhance insignificant contours. To partially address this drawback, we introduce here a fully unsupervised multi-scale approach including bagging. Re-sampling and bagging is a classical stochastic approach to improve the estimation. We have assessed the performance, and compared to other version of stochastic watershed, using the Berkeley segmentation database.
KW - Berkeley segmentation database
KW - Stochastic watershed
KW - Unsupervised image segmentation
U2 - 10.1007/978-3-319-18720-4_36
DO - 10.1007/978-3-319-18720-4_36
M3 - Conference contribution
AN - SCOPUS:84945972016
SN - 9783319187198
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 422
EP - 433
BT - Mathematical Morphology and its Applications to Signal and Image Processing - 12th International Symposium, ISMM 2015, Proceedings
A2 - Najman, Laurent
A2 - Talbot, Hugues
A2 - Benediktsson, Jon Atli
A2 - Chanussot, Jocelyn
PB - Springer Verlag
T2 - 12th International Symposium on Mathematical Morphology, ISMM 2015
Y2 - 27 May 2015 through 29 May 2015
ER -