DeepAI AI Chat
Log In Sign Up

Segmentation hiérarchique faiblement supervisée

by   Amin Fehri, et al.

Image segmentation is the process of partitioning an image into a set of meaningful regions according to some criteria. Hierarchical segmentation has emerged as a major trend in this regard as it favors the emergence of important regions at different scales. On the other hand, many methods allow us to have prior information on the position of structures of interest in the images. In this paper, we present a versatile hierarchical segmentation method that takes into account any prior spatial information and outputs a hierarchical segmentation that emphasizes the contours or regions of interest while preserving the important structures in the image. An application of this method to the weakly-supervised segmentation problem is presented.


page 3

page 4


Prior-based Hierarchical Segmentation Highlighting Structures of Interest

Image segmentation is the process of partitioning an image into a set of...

The VOISE Algorithm: a Versatile Tool for Automatic Segmentation of Astronomical Images

The auroras on Jupiter and Saturn can be studied with a high sensitivity...

ACCL: Adversarial constrained-CNN loss for weakly supervised medical image segmentation

We propose adversarial constrained-CNN loss, a new paradigm of constrain...

Weakly Supervised Segmentation by A Deep Geodesic Prior

The performance of the state-of-the-art image segmentation methods heavi...

Estimating Appearance Models for Image Segmentation via Tensor Factorization

Image Segmentation is one of the core tasks in Computer Vision and solvi...

Hierarchical image simplification and segmentation based on Mumford-Shah-salient level line selection

Hierarchies, such as the tree of shapes, are popular representations for...

Large-scale image segmentation based on distributed clustering algorithms

Many approaches to 3D image segmentation are based on hierarchical clust...