The experimental Automated Ship Image Acquisition System (ASIA) collects high-resolution ship photographs at a
shore-based laboratory, with minimal human intervention. The system uses Automatic Identification System (AIS) data
to direct a high-resolution SLR digital camera to ship targets and to identify the ships in the resulting photographs. The
photo database is then searchable using the rich data fields from AIS, which include the name, type, call sign and various
vessel identification numbers. The high-resolution images from ASIA are intended to provide information that can
corroborate AIS reports (e.g., extract identification from the name on the hull) or provide information that has been
omitted from the AIS reports (e.g., missing or incorrect hull dimensions, cargo, etc). Once assembled into a searchable
image database, the images can be used for a wide variety of marine safety and security applications. This paper
documents the author's experience with the practicality of composing photographs based on AIS reports alone,
describing a number of ways in which this can go wrong, from errors in the AIS reports, to fixed and mobile obstructions
and multiple ships in the shot. The frequency with which various errors occurred in automatically-composed
photographs collected in Halifax harbour in winter time were determined by manual examination of the images. 45% of
the images examined were considered of a quality sufficient to read identification markings, numbers and text off the
entire ship. One of the main technical challenges for ASIA lies in automatically differentiating good and bad
photographs, so that few bad ones would be shown to human users. Initial attempts at automatic photo rating showed
75% agreement with manual assessments.
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