A new Segmentation Approach for Unimodal Image Histograms: Application to the Detection of Regions of Interest in Sonar Images

Imen Mandhouj (1, 2, 3) , Frederic Maussang (1, 3) , Basel Solaiman (1) , Hamid Amiri (2)

1 ITI - Département Image et Traitement Information
2 LSTS - Laboratoire des Systèmes et du Traitement du Signal [ENIT]
3 Lab-STICC_TB_CID_TOMS

The purpose of our work is to define an original approach to determine the threshold of unimodal image histograms in a robust manner. Our proposed segmentation approach refers to Shannon entropy. Threshold estimation is based on the exploitation of the curve of the entropy loss quantity. The final expression of the sigmoid estimated function of the entropy error and derivatives are used to select the image's threshold segmentation. The proposed approach is evaluated on a set of SAS (Synthetic Aperture Sonar) images.

Mots clés: Sonar image; Unimodal thresholding; Entropy error function; Logistic function; Sigmoidal curve

Domaines: Traitement du signal et de l'image [eess.SP]

Imen Mandhouj, Frederic Maussang, Basel Solaiman, Hamid Amiri. A new Segmentation Approach for Unimodal Image Histograms: Application to the Detection of Regions of Interest in Sonar Images. OCEANS 2014 - St John's : MTS/IEEE international conference, Sep 2014, St. John'S, Nl, Canada. ⟨hal-01188940⟩