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Pseudo Invariant Line Moment to Detect the Target Region of Moving Vessels

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5754))

Abstract

In order to get the features of moving vessels at the port correctly and track the target quickly and efficiently, we combined the advantages of traditional invariant moments and invariant line moments, and proposed a object recognition algorithm based on pseudo invariant line moments. Using this algorithm, first we get the calculation regions of the objects in an image, then do edge detection to the calculation regions and get the pseudo invariant line moments by calculating binary image. The experimental results show that the algorithm can not only get the regions of moving objects quickly and accurately, but also can predict the directions of moving objects effectively. This algorithm is applied in the intelligent video monitoring system of moving vessels successfully.

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References

  1. Valera, M., Velastin, S.A.: Intelligent Dstributed Srvuillance Systems A Review. IEEE Proceeding of Vision, Image, and Signal Processing 2005 152(2), 192–204 (2005)

    Article  Google Scholar 

  2. Frauel, Y., Quesada, O., Bribiesca, E.: Detection of a Polymorphic Mesoamerican Symbol Using a Rule-based Approach. Pattern Recognition 39(7), 1380–1390 (2006)

    Article  Google Scholar 

  3. Hu, M.K.: Visual Pattern Recognition by Moment Invariants. IRE Transactions on Information Theory 8(2), 179–187 (1962)

    Article  Google Scholar 

  4. Oliveira, R.J., Ribeiro, P.C., et al.: A Video System for Urban Surveillance: Function Integration and Evaluation. In: International Workshop on Image Analysis for Multimedia Interactive Systems (2004)

    Google Scholar 

  5. Alirezaee, S., Aghaeinia, H., Ahmadi, M., Faez, K.: Recognition of Middle Age Persian Characters Using a Set of Invariant Moments. In: Proceedings of the 33rd Applied Imagery Pattern Recognition Workshop (2004)

    Google Scholar 

  6. Parodies, T., Ali, F.: Computer Recognition of Handwritten Numerals by Polygonal Approximations. IEEE Transactions on Systems, Man, Cyber SMC26, 610–614 (1975)

    Google Scholar 

  7. Shamsuddin, M., Sulaiman, M.N., Darus, M.: Improved Scale-invariant Moments for Deformation Digits. International Journal of Computer Mathematics, 439–447 (2000)

    Google Scholar 

  8. Analysis and Invariant Moments. WSEAS Transactions on Information Science and Applications 10, 2066–2077 (2006)

    Google Scholar 

  9. Lin, H.B., Si, J., Abousleman, G.P.: Orthogonal Rotation-invariant Moments for Digital Image Processing. IEEE Transactions on Image Processing 3, 272–282 (2008)

    MathSciNet  Google Scholar 

  10. Dhandra, B.V., Malemath, V.S., Mallikarjun, H., Hegadi, R.: Multi-font English Character Recognition Based on Modified Invariant Moments. Journal of Combinatorial Mathematics and Combinatorial Computing 67, 153–162 (2008)

    MATH  Google Scholar 

  11. Li, X.M., Shi, Z.Y.: Ellipses and Circles Recognition Based on Invariant Moments. Beijing Gongye Daxue Xuebao / Journal of Beijing University of Technology 11, 1136–1140 (2007)

    Google Scholar 

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© 2009 Springer-Verlag Berlin Heidelberg

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Ke, J., Zhan, Y., Chen, X., Wang, M. (2009). Pseudo Invariant Line Moment to Detect the Target Region of Moving Vessels. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2009. Lecture Notes in Computer Science, vol 5754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04070-2_67

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  • DOI: https://doi.org/10.1007/978-3-642-04070-2_67

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04069-6

  • Online ISBN: 978-3-642-04070-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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