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Ocean Systems Engineering Volume 4, Number 1, March 2014 , pages 53-62 DOI: https://doi.org/10.12989/ose.2014.4.1.053 |
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A novel approach of ship wakes target classification based on the LBP-IBPANN algorithm |
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Liu Bo, Lin Yan and Zhang Liang
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| Abstract | ||
| The detection of ship wakes image can demonstrate substantial information regarding on a ship, such as its tonnage, type, direction, and speed of movement. Consequently, the wake target recognition is a favorable way for ship identification. This paper proposes a Local Binary Pattern (LBP) approach to extract image features (wakes) for training an Improved Back Propagation Artificial Neural Network (IBPANN) to identify ship speed. This method is applied to sort and recognize the ship wakes of five different speeds images, the result shows that the detection accuracy is satisfied as expected, the average correctness rates of wakes target recognition at the five speeds may be achieved over 80%. Specifically, the lower ship\'s speed, the better accurate rate, sometimes it\'s accuracy could be close to 100%. In addition, one significant feature of this method is that it can receive a higher recognition rate than the nearest neighbor classification method. | ||
| Key Words | ||
| ship wake; target classification; Local Binary Patterns; BP artificial neural network model | ||
| Address | ||
| Liu Bo and Lin Yan : State Key Laboratory of Structural Analysis for Industrial Equipment, School of Naval Architecture and Ocean Engineering, Dalian University of Technology, 116024 Dalian, P.R. China Zhang Liang: Yantai HUF Automobile Lock Co. Ltd., 264006 Yantai, P.R. China | ||
