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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.
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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


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


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



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