A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects

Kulikova, M.S.; Jermyn, I.H.; Descombes, X.; Zhizhina, E.; Zerubia, J.

Abstract

We define a method for incorporating strong prior shape information into a recently extended Markov point process model for the extraction of arbitrarily-shaped objects from images. To estimate the optimal configuration of objects, the process is sampled using a Markov chain based on a stochastic birth-and-death process defined in a space of multiple objects. The single objects considered are defined by both the image data and the prior information in a way that controls the computational complexity of the estimation problem. The method is tested via experiments on a very high resolution aerial image of a scene composed of tree crowns.

Citation

Kulikova, M., Jermyn, I., Descombes, X., Zhizhina, E., & Zerubia, J. (2009, December). A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects. Presented at Fifth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 2009, Marrakesh

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Fifth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 2009
• Publication Date: Dec 1, 2009
• Deposit Date: Aug 12, 2011
• Publicly Available Date: Apr 15, 2016
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 180-186
• Book Title: The Fifth International Conference on Signal Image Technology & Internet Based Systems SITIS 2009 ; proceedings
• DOI: https://doi.org/10.1109/sitis.2009.38
• Public URL: https://durham-repository.worktribe.com/output/1158080