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Detection and amendment of shape distortions based on moment invariants for active shape models

Detection and amendment of shape distortions based on moment invariants for active shape models

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The active shape model (ASM) is an ever-increasingly important method for object modelling, shape recognition and target localisation. During the process of shape fitting, however, distortions and displacements often occur when the target is not clear or with defects, and there is a lack of effective amendment strategies in ASM. In this study, inspired by physics, the boundary moment invariants are employed to resolve this difficulty. Moment invariants have been introduced into ASM for the first time for distortion detection and shape amendment. Using the proposed strategy, distortions are effectively avoided and the accuracy of the fitting result is obviously increased with a little extra time. Finally, the results of the authors' practical implementation prove its satisfactory work.


    1. 1)
      • M. Muharrem , G. Kayhan , M. Tarik Veli . Real object recognition using moment invariants. Acad. Proc. Eng. Sci. , 765 - 775
    2. 2)
      • R. Mukundan , K.R. Ramakrishnan . (1998) Moment functions in image analysis.
    3. 3)
    4. 4)
    5. 5)
    6. 6)
      • Hamarneh, G.: `Active shape models, modeling shape variations and gray level information and an application to image search and classification', R005/1998, Technical, 1998.
    7. 7)
    8. 8)
      • Z.Y. Yu , X.J. Li . Research on stored – grain microbe S recognition based on moment invarian. Control Autom. , 251 - 253
    9. 9)
      • M.K. Hu . Visual pattern recognition by moment invariants. IEEE Trans. Inf. Theory , 179 - 187
    10. 10)
      • Wang, W., Shan, S.G., Gao, W., Cao, B., Yin, B.C.: `An improved active shape model for face alignment', Fourth IEEE Int. Conf. on Multimodal Interfaces, October 2002, Pittsburgh, USA, p. 523–528.
    11. 11)
      • P. Du , Y.K. Zhang , C.Q. Liu . A face recognition method based on moment invariants. Comput. Simul. , 78 - 81
    12. 12)
    13. 13)
    14. 14)
    15. 15)
      • de Bruijne, M., van Ginneken, B., Niessen, W.J., Viergever, M.A.: `Active shape model segmentation using a non-linear appearance model: application to 3D AAA segmentation', UU-CS-2003–013, Technical Report, 2003.
    16. 16)
      • Z.L. Wang , Zh.C. Mu , X.Y. Wang , H.T. Mi . Ear recognition based on moment invariants. Pattern Recognit. Artif. Intell. , 502 - 505

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