Synthetic aperture sonar images segmentation using dynamical modeling analysis

Luis Américo Conti, Murilo Baptista

Research output: Contribution to journalArticlepeer-review


Symbolic Models applied to Synthetic Aperture Sonar images are proposed in order to assess the validity and reliability of use of such models and evaluate how effective they can be in terms of image classification and segmentation. We developed an approach for the description of sonar images where the pixels distribution can be transformed into points in the symbolic space in a similar way as symbolic space can encode a trajectory of a dynamical system. One of the main characteristic of approach is that points in the symbolic space are mapped respecting dynamical rules and, as a consequence, it can possible to calculate quantities that characterize the dynamical system, such as Fractal Dimension (D), Shannon Entropy (H) and the amount of information of the image. It also showed potential to classify image sub-patterns based on the textural characteristics of the seabed. The proposed method reached a reasonable degree of success with results compatible with the classical techniques described in literature.

Original languageEnglish
Pages (from-to)455-462
Number of pages8
JournalRevista Brasileira de Geofisica
Issue number3
Publication statusPublished - 1 Jan 2013


  • Dynamical models
  • Fractal
  • Image processing
  • Seabed segmentation
  • Synthetic aperture sonar


Dive into the research topics of 'Synthetic aperture sonar images segmentation using dynamical modeling analysis'. Together they form a unique fingerprint.

Cite this