For active contour modeling (ACM), we propose a novel self-organizing map (SOM)-based
approach, called the batch-SOM (BSOM), that attempts to integrate the advantages of SOM …

We integrate the advantages of SOM-and snake-based ACMs in order to extract the desired
contour from images. We employ:(i) the feature points to guide the contour, as in the case of …

Active contour models (ACMs) are popular and widely used for many image segmentation
applications and obtain promising results. However, these methods are unable to achieve …

A new online region-based active contour model (ORACM) is proposed in this paper. The
classical geodesic active contour (GAC) model has only local segmentation property …

Abstract Active Contour Models (ACM s) constitute a powerful energy-based minimization
framework for image segmentation, based on the evolution of an active contour. Among …

Abstract Self Organizing Maps (SOM s) have attracted the attention of many computer vision
scientists, particularly when dealing with image segmentation as a contour extraction …

Contour finding of distinct features in 2-D/3-D images is essential for image analysis and
computer vision. To overcome the potential problems associated with existing contour …

Active contour modeling is a powerful technique for modeling object boundaries. Various
methods introduced for this purpose, however, have certain difficulties such as getting stuck …

Supervised active contour models can use information extracted from supervised samples to
guide contour evolution. However, their applicability is limited by the accuracy of the …

Image segmentation using a region-based active contour model could present difficulties
when its noise distribution is unknown. To overcome this problem, this paper proposes a …