HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

Segmentation hiérarchique faiblement supervisée

Abstract : 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.
Complete list of metadata

Cited literature [8 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01711811
Contributor : Amin Fehri Connect in order to contact the contributor
Submitted on : Monday, February 19, 2018 - 9:32:36 AM
Last modification on : Wednesday, November 17, 2021 - 12:27:15 PM
Long-term archiving on: : Monday, May 7, 2018 - 1:08:41 PM

Files

FEHRI_GRESTI17.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01711811, version 1
  • ARXIV : 1802.07008

Citation

Amin Fehri, Santiago Velasco-Forero, Fernand Meyer. Segmentation hiérarchique faiblement supervisée. 26e colloque GRETSI, Sep 2017, Juan-les-Pins, France. ⟨hal-01711811⟩

Share

Metrics

Record views

2666

Files downloads

103