Object Classification via Geometrical , Zernike and Legendre Moments

@inproceedings{Arif2009ObjectCV,
  title={Object Classification via Geometrical , Zernike and Legendre Moments},
  author={Thawar Arif and Zyad Shaaban and LALA KREKOR and Sami E. I. Baba},
  year={2009}
}
In many applications, different kinds of moments have been utilized to classify images and object shapes. Moments are important features used in recognition of different types of images. In this paper, three kinds of moments: Geometrical, Zernike and Legendre Moments have been evaluated for classifying 3D object images using Nearest Neighbor classifier. Experiments are conducted using ETH-80 database, which contains 80 objects. 
Highly Cited
This paper has 22 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.
16 Citations
36 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 16 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 36 references

Chora ́s, Image Feature Extraction Techniques and Their Applications for CBIR and Biometrics Systems, INTERNATIONAL JOURNAL OF BIOLOGY AND BIOMEDICAL ENGINEERING

  • S. Ryszard
  • Issue 1,
  • 2007
Highly Influential
4 Excerpts

Image analysis via the general theory of moments

  • M. Teague
  • J. Opt Soc. Am. 70 (8)
  • 1980
Highly Influential
6 Excerpts

The shape recognition based on structure moment invariants

  • Li Zongmin, Kunpeng Hou, Liu Yujie, Diao Luhong, Li Hua
  • International Journal of Information Technology,
  • 2006
1 Excerpt

Similar Papers

Loading similar papers…