Authors:
Abdel-Ouahab Boudraa
1
and
Jean-Christophe Cexus
2
Affiliations:
1
IRENav, Ecole Navale & E3 I2 , (EA 3876) ENSIETA, France
;
2
IUT de Lannion, France
Keyword(s):
Image segmentation, Gabor filtering, Clustering, Feature selection, Texture, Sonar image.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Image Filtering
;
Image Formation and Preprocessing
;
Segmentation and Grouping
Abstract:
In this work an unsupervised Sonar (Sound navigation and ranging) images segmentation is proposed. Due to
the textural nature of the Sonar images, a band-pass filtering that takes into account the local spatial frequency
of these images is proposed. Sonar image is passed through a bank of Gabor filters and the filtered images that possess a significant component of the original image are selected. To calculate the radial frequencies, a new approach is proposed. The selected filtered images are then subjected to a non-linear transformation. An energy measure is defined on the transformed images in order to compute texture features. The texture energy features are used as input to a clustering algorithm. The segmentation scheme has been successfully tested on real
high-resolution Sonar images, yielding very promising results.