Ship detection and tracking is a basic task in any vessel traffic monitored area, whether marine or inland. It has a major impact on navigational safety and thus different systems and technologies are used to determine the best possible methods of detecting and identifying sailing units. Video monitoring is present in almost all of them, but it is usually operated manually and is used as a backup system. This is because of the difficulties in implementing an efficient and universal automatic detection method that would work in quickly alternating environmental conditions for all kind of sailing units—from kayaks to seagoing merchant vessels. This paper presents a method that allows the detection and tracking of ships using the video streams of existing monitoring systems for ports and rivers. The method and the results of experiments on three sets of data using cameras with different characteristics, settings, and scene locations are presented. The experiments were carried out in variable light and weather conditions, and a wide range of unit types were used as detection objectives. The results confirm the usability of the proposed solution; however, some minor issues were encountered in the presence of ships wakes or highly unfavourable weather conditions.

The article presents the watercraft recognition and identification system as an extension for the presently used visual water area monitoring systems, such as VTS (Vessel Traffic Service) or RIS (River Information Service). The watercraft identification systems (AIS - Automatic Identification Systems) which are presently used in both sea and inland navigation require purchase and installation of relatively expensive transceivers on ships, the presence of which is not formally required as equipment of unconventional watercrafts, such as yachts, motor boats, and other pleasure crafts. These watercrafts may pose navigation or even terrorist threat, can be the object of interest of the customs, or simply cause traffic problems on restricted water areas. The article proposes extending the traffic supervision system by a module which will identify unconventional crafts based on video monitoring. Recognition and identification will be possible through the use of image identification and processing methods based on artificial intelligence algorithms, among other tools. The system will be implemented as independent service making use of the potential of SOA (Service Oriented Architecture) and XML/SOAP (Extensible Markup Language/Simple Object Access Protocol) technology.

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The article presents a method to determine the position of mechanically scanned sonar images by comparing them with the database of simulated synthetic images. The synthetic images are generated from high-density bathymetric data coming from the same fragment of water region, using the ray tracing method. The article discusses the issues related to the choice of the probability function as the method of image comparing which allows to find the correct georeference of the real image. For the correlation method and the logical conjunction method, which are believed to give the best results, detailed studies were performed, including boundary cases. The obtained results of matching are presented in tabular and graphic form.

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