# Speckled Images Segmentation and Algorithm Comparison

### Luigi Cinque, Rossella Cossu, Rosa Maria Spitaleri

#### Abstract

An image segmentation process, based on the level set method, consists in the time evolution of an initial curve until it reaches the boundary of the objects to be extracted. Classically the evolution of the initial curve is determined by a speed function. In this paper, the speed in the level set procedure is characterized by the combination of two different speed functions and the resulting algorithm is applied to speckled images, like SAR (Synthetic Aperture Radar) images. In order to assess improvements of the segmentation performance, the computational process is tested on synthetic and then applied to real images. Performances are evaluated on synthetic images by using the Hausdorff distance. The real SAR images were acquired during the ERS2 mission.

#### References

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#### Paper Citation

#### in Harvard Style

Cinque L., Cossu R. and Maria Spitaleri R. (2015). **Speckled Images Segmentation and Algorithm Comparison** . In *Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,* ISBN 978-989-758-077-2, pages 111-118. DOI: 10.5220/0005166901110118

#### in Bibtex Style

@conference{icpram15,

author={Luigi Cinque and Rossella Cossu and Rosa Maria Spitaleri},

title={Speckled Images Segmentation and Algorithm Comparison},

booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},

year={2015},

pages={111-118},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0005166901110118},

isbn={978-989-758-077-2},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,

TI - Speckled Images Segmentation and Algorithm Comparison

SN - 978-989-758-077-2

AU - Cinque L.

AU - Cossu R.

AU - Maria Spitaleri R.

PY - 2015

SP - 111

EP - 118

DO - 10.5220/0005166901110118