TELECOMMUNICATIONS AND RADIO ENGINEERING - 2009 Vol. 68,
No 9
 

 

 

 

Image Likelihood Measures on the Basis of the Set of Conformities

V.À. Gorokhovatsky and Ye.P. Putyatin
Kharkiv National University of Radio Engineering and Electronics, 14, Lenin Ave, Kharkiv, 61166, Ukraine

Abstract
The structural methods for analysis of images in the systems of computer vision are considered. The likelihood measures considering the influence of local distortions and occurrence of false components in the structural description are suggested. The methods of filtration on the basis of geometrical information as a means for elimination of false attributes are described. The analysis of the properties of the methods is performed, the results of computer modeling for real images are described.

References

  1. Shapiro, L., (2001), Computer vision, Prentice Hall, - 625 p.
  2. Lowe, D.G., (2004), Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision. 60(2):91-110.
  3. Putyatin, Ye.P., Gorokhovatsky, V.À., and Kuzmin, S.V., (2006), Recognition of images in the space of invariant local attributes, Radio Electronics and Informatics. 1(32):69-73 (in Russian).
  4. Gorokhovatsky, V.À., (2008), Hierarchy of spatial interrelations between structural attributes in the problems of comparison of visual objects, Systems of control, navigation and communication. 3(7):85-89 (in Russian).
  5. Gorokhovatsky, V.À., and Putyatin, Ye.P., (2008), Structural recognition of images on the basis of voting models of attributes of typical points, Data recording, storage and processing. 10(4):75-85 (in Russian).
  6. http://www1.cs.columbia.edu/CAVE/software/softlib/coil-20.php
  7. Àyvazyan, S.À., Buchstaber, V.Ì., Yenyukov, I.S., and Ìåshalkin, L.D., (1989), Applied statistics: Classification and decreasing of dimensions. Finance and statistics, Moscow: 607 p. (in Russian).
  8. Duda, R.O., Hart, P.E., and Stork, D.G., (2000), Patternclassification, Wiley, - 738p.
  9. Putyatin, Ye.P., Gorokhovatsky, V.À., and Ìàtàt, Î.Î., (2006), Ìethods and algorithms of computer vision, SMIT Company Ltd., Kharkiv: 236 p. (in Russian).
  10. Putyatin, Ye., Gorohovatsky, V., Gorohovatsky, A., and Peredriy, E., (2008), Projective methods of image recognition, Intelligent Technologies and Application. Sofia: FOI ITHEA. 5:37–43.
  11. Sytnik, O.V., and Gorohovatsky, A.V., (2007), Signal processing algorithms in identification of subsurface objects, Radioelectronics and Communications Systems, 50(10):557-563.
  12. Kinoshenko, D., Mashtalir, V., and Shlyakhov, V., (2007), A Partition Metric for Clustering Features Analysis, Int. J. Information Theories and Applications. 14(3):230-236.


pages 763-778

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