Moving Ships Detection And Tracking From Infrared Image In Inland Waterway

The recent growth in inland waterway shipping traffic has resulted in a concomitant increase in the risk of shipping accidents, thus making collision avoidance a critical issue in inland waterway shipping traffic safety. The main reason resulted in ships collision is sailing under the restricted visibility conditions such as fog, mist, night and etc. The key of collision avoidance for the reference ship or the bridge, in which FLIR equipments is equipped, is to obtain accuracy navigation information about target ships which locate in front of the reference ship. The forward-looking infrared (FLIR) images have a lot of advantage, such as the capacity of resisting disturbance and the adaptability of weather is strong, the ability of passive detection is continuous day and night. The uncooled infrared focal plane arrays (FGA) FLIR camera, which have lower price and technical matured, is installed on the importance location such as in front of ship, bridge pier, strobe, the restricted area in the river. When infrared images are captured by real time, various technologies that include image processing, object detection, object tracking and etc are integrated and used to robust process and analyze these images in real time way. So, it can be achieved to detection and tracking other moving ships in inland waterway under poorly visible conditions. The detection and tracking other moving ships information are applied to assist sailing for ship. These information are used to improve the capability of apperception for ship's driver and inspector, to assist ship's driver decision for avoidance collision, to reduce driving mistake, to enhance the success ratio to avoid ship-ship or ship-bridge collision. Then, People casualty is safeguarded. The damage of ship, bridge and goods are avoided. Economical, social and environmental loss are reduced or avoided furthermore. Finally, the safety sailing is ensured.There are three critical steps in surveillance system analysis based on video frequency, i.e. interesting of moving object detection, object tracking and object's behavior recognition based on object's trial analyzed. Object detection and tracking from infrared image, which restrict and bother the practical detection performance, is one of the key stages in intelligent information processing field. It is a bottleneck problem and a technical difficulty unsolved. Meanwhile, when the infrared technology is used to transportation security in inland waterway, the critical technology should be solved is moving ship detection and tracking from infrared image firstly. To sum up, moving ships detection and tracking from infrared image in inland waterway have not only importance practical worthiness but also importance science research value.Firstly, the principle, components and advantage of FLIR system are introduced. The infrared characteristic of Ship and background in inland waterway are qualitative analyzed. The characteristic of noise in infrared image is analyzed. The performance of object detection and tracking algorithm is presented.Secondly, a method is proposed to extract and assessment the sky-water line under complicated inland waterway background based on understanding the existing methods. The result of experiment shows that the proposed method has wide adaptability and high precision, and it has fulfilled the demand of real-time and reliability.Thirdly, a review of man-made object detection algorithms is presented based on various fractal features, which are derived from the blanket covering method. Based on the review, a new multi-scale fractal feature parameter, i.e. multi-scale fractal feature related with K (MFFK), is presented. The results of experiments show that in MFFK image calculated from original infrared image performs the best discriminating capability between natural background and man-made object in fractal feature images.Furthermore, ship detection algorithm in inland waterway based on MFFK is presented. Experimental results have shown that the approach is feasible and effective under complicated inland waterway background. It has achieved real-time and reliable ship detection.Fourthly, mean shift algorithm is introduced. Then a moving ship tracking algorithm in inland waterway is proposed based on mean shift algorithm. The significant characteristic of the algorithm is that MFFK image is used to describe moving ship in inland waterway. Experimental results have shown that the proposed algorithm is effective and robust for tracking single moving ship in inland waterway from infrared image. Moreover, it is satisfied the request of real time tracking. However, the reliability of the proposed algorithm is going to depress due to ship-to-ship occlusions.Fifthly, the method and theory related to particle filter are surveyed. The applications of particle filter in object tracking field based on video sequence are reviewed. Then, a moving ship tracking algorithm is proposed based on single gray characteristic. Under the theory framework of particle filter, the posterior distribution of the moving ship in MFFK image is approximated by a set of weighted samples, while the moving ship tracking is implemented by the Bayesian propagation of the sample set. Experimental results have shown that the moving ship in inland waterway is not enough approximated by single gray feature. The proposed algorithm can be used in simple inland waterway background, and it isn't applied in clutter inland waterway background.Sixth, the characteristics of moving ship silhouette, shape and texture in infrared image are generally unobvious in inland waterway. Furthermore, the moving ship in inland waterway is not enough described by single gray feature. So, fusion between gray feature and moving cue is presented for approximating moving ship in inland waterway. The gray feature of moving ship is extracted from MFFK image; the moving cue of moving ship is obtained by differencing between two MFFK image frames. The comparability coefficient of multi-characteristic fusion can be obtained by fusing between gray feature and moving cue based on fuzzy logic. Finally, a moving ship tracking algorithm is proposed based on characteristic fusion between gray feature and moving cue under the theory framework of particle filter. The algorithm is integrated with fractal geometry, mean shift, temporal differences method, particle filter, fuzzy, etc. Experimental results have shown that the proposed algorithm is not only used to tracking moving ship in complicated inland waterway background steadily, but also adapted to changing moving ship and the scene, non-rigid ship structures, ship-to-ship and ship-to-scene occlusion. The proposed algorithm is effective and robust. Moreover, it is satisfied the request of real time tracking due to require a low number of particles from the prior in real applications.Finally, the summary of the thesis is given. Furthermore, the further work and research prospects are introduced.