Marked Point Process Model for Curvilinear Structures Extraction

Seong-Gyun Jeong 1 Yuliya Tarabalka 2, 1 Josiane Zerubia 1
2 TITANE - Geometric Modeling of 3D Environments
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : In this paper, we propose a new marked point process (MPP) model and the associated optimization technique to extract curvilinear structures. Given an image, we compute the intensity variance and rotated gradient magnitude along the line segment. We constrain high level shape priors of the line segments to obtain smoothly connected line configuration. The optimization technique consists of two steps to reduce the significance of the parameter selection in our MPP model. We employ Monte Carlo sampler with delayed rejection to collect line hypotheses over different parameter spaces. Then, we maximize the consensus among line detection results to reconstruct the most plausible curvilinear structures without parameter estimation process. Experimental results show that the algorithm effectively localizes curvilinear structures on a wide range of datasets.
Document type :
Conference papers
Complete list of metadatas

Cited literature [31 references]  Display  Hide  Download

https://hal.inria.fr/hal-01084939
Contributor : Seong-Gyun Jeong <>
Submitted on : Tuesday, January 27, 2015 - 10:52:39 AM
Last modification on : Thursday, January 11, 2018 - 4:49:43 PM

Identifiers

Collections

Citation

Seong-Gyun Jeong, Yuliya Tarabalka, Josiane Zerubia. Marked Point Process Model for Curvilinear Structures Extraction. EMMCVPR 2015, Jan 2015, Hong Kong, Hong Kong SAR China. pp.436-449, ⟨10.1007/978-3-319-14612-6_32⟩. ⟨hal-01084939⟩

Share

Metrics

Record views

496

Files downloads

322