PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Bedini L., Righi M., Salerno E. OSIRIS - Segmentation, ship identification and ship size estimation from high-resolution SAR imagery. Optical/SAR data and system Integration for Rush Identification of Ship models. Project report 2, 2017.
 
 
Abstract
(English)
This report summarizes our proposals and results on problems posed by the software module 2 (Ship Classification, or SC) of the OSIRIS system. From the UML specification, the computational part of this module includes five phases: a) Segmentation; b) Shape recognition; c) Size estimation; d) Ship classification; e) Final estimation. Phases d) and e) have been assigned to an advanced classification submodule based on a ground-truth database, already devised in Salerno (2016), which will be the subject of a separate report. In the following, we deal with Segmentation-Shape recognition and Size estimation, where ``shape recognition'' means identifying the component of the segmented image that most likely contains the SAR ship footprint. The keys to the proposed processing are an adaptive-threshold segmentation followed by a maximum-area connected component detection, and the identification of the fore-and-aft line of the ship as the axis of minimum inertia with respect to the connected component barycenter. Once this axis has been found, the size-estimation phase is intended to find the ship length overall and beam overall. Our solution to this problem is to approximate a minimum-area rectangle enclosing the target and leaving out as many artifacts as possible. To this end, we devised two iterative strategies, taking into account that a ship has normally a well-defined, not general, shape. The principal inertia axis at the last iteration is also an estimate of the ship heading with a 180-degree ambiguity.
Subject SAR Image processing
I.5.1 PATTERN RECOGNITION. Models


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