Paper Info
Title
Safer Navigation of Ships by Image Processing & Neural Network
Abstract
In Today’s modern era Safer Navigation has become a major issue since most of our overseas logistics depends on floating vessels. In this paper an algorithm has been developed to classify the ships according to there dimension by using image processing. The image of the ship has been recorded by a stationary camera. We extract and calculate the dimension and parameters of the ship by using categories; small, medium and large. We use a feed forward neural network trained using the back-proportion learning algorithm to classify the ships. The experimental results are provided by actual data of ship which demonstrate the effectiveness of the method. Moreover, this method is presented to recognize the type of ship and also provide the graphical user interface (GUI) which allows to simulate the classified results. The papers also discuss the present condition of Marine Watch System and give some issues to be considered. The objective of this study is to achieve the integration of the traditional navigation equipment with an image processing system.
Year
DOI
Venue
2008
10.1109/AMS.2008.48
Asia International Conference on Modelling and Simulation
Keywords
Field
DocType
actual data,marine watch system,neural network,image processing,image processing system,major issue,graphical user interface,classified result,floating vessel,safer navigation,graphic user interface,feedforward neural networks,logistics,feed forward neural network,marine engineering,data mining,graphical user interfaces,backpropagation,neural networks,navigation,image segmentation
Data mining,Computer vision,Feedforward neural network,Computer science,Image processing,SAFER,Image segmentation,Graphical user interface,Artificial intelligence,Backpropagation,Artificial neural network
Conference
ISBN
Citations 
PageRank 
978-0-7695-3136-6
0
0.34
References 
Authors
3
3
Name
Order
Citations
PageRank
G. K. Santhalia121.45
Sanatya Singh210.72
Satish Kumar Singh322417.23