International audienceIn this work, we propose a stochastic model for curvilinear structure reconstruction using morphological profiles of path opening operator. We apply the support vector machine classifier to obtain initial probabilities to belong to line network for each pixel. Then, we formulate a stochastic optimization problem that detects line segments corresponding to the latent curvilinear structure in a scene. Experimental results on DNA filament and remote sensing images validate the effectiveness of the proposed algorithm when compared to other recent methods
We propose a new approach to semi-automated delin-eation of curvilinear structures in a wide range o...
Extracting meaningful information from digital images, and in particular from curvilinear structures...
The detection of curvilinear structures is an important step for various computer vision application...
In this dissertation, we propose curvilinear structure reconstruction models based on stochastic mod...
Dans cette thèse, nous proposons des modèles de reconstruction de la structure curviligne fondée sur...
International audienceIn this paper, we propose a new marked point process (MPP) model and the assoc...
To detect curvilinear structures in natural images, we propose a novel rankinglearning system and an...
Reconstructing complex curvilinear structures such as neural circuits, road networks, and blood vess...
International audienceFilamentary structures extraction in medical and biological images is a challe...
We propose a novel tree-like curvilinear structure reconstruction algorithm based on supervised lear...
This paper presents a general framework to segment curvilinear objects in 2D images. A pre-processin...
Natura scenes consist of a wide variety of stochastic patterns. While many patterns are represented ...
Active contours and active shape models have been widely employed in bio- medical image segmentatio...
Abstract. This paper presents a general framework to segment curvi-linear objects in 2D images. A pr...
This paper is concerned with a new technique of curve fitting. The technique has various phases incl...
We propose a new approach to semi-automated delin-eation of curvilinear structures in a wide range o...
Extracting meaningful information from digital images, and in particular from curvilinear structures...
The detection of curvilinear structures is an important step for various computer vision application...
In this dissertation, we propose curvilinear structure reconstruction models based on stochastic mod...
Dans cette thèse, nous proposons des modèles de reconstruction de la structure curviligne fondée sur...
International audienceIn this paper, we propose a new marked point process (MPP) model and the assoc...
To detect curvilinear structures in natural images, we propose a novel rankinglearning system and an...
Reconstructing complex curvilinear structures such as neural circuits, road networks, and blood vess...
International audienceFilamentary structures extraction in medical and biological images is a challe...
We propose a novel tree-like curvilinear structure reconstruction algorithm based on supervised lear...
This paper presents a general framework to segment curvilinear objects in 2D images. A pre-processin...
Natura scenes consist of a wide variety of stochastic patterns. While many patterns are represented ...
Active contours and active shape models have been widely employed in bio- medical image segmentatio...
Abstract. This paper presents a general framework to segment curvi-linear objects in 2D images. A pr...
This paper is concerned with a new technique of curve fitting. The technique has various phases incl...
We propose a new approach to semi-automated delin-eation of curvilinear structures in a wide range o...
Extracting meaningful information from digital images, and in particular from curvilinear structures...
The detection of curvilinear structures is an important step for various computer vision application...