OBJECTS IMAGES ALIGNMENT WITH THE USE OF GENETIC AND GRADIENT ALGORITHMS

Authors

  • Sergiy Balovsyak
  • Igor Fodchuk

DOI:

https://doi.org/10.47839/ijc.12.2.597

Keywords:

digital images, images alignment, genetic algorithms, chromosome, mutation, gradient algorithms.

Abstract

The given paper presents a hybrid method which is a combination of genetic and gradient algorithms used for the comparison of digital images of an object. Aligning the images, their basic transformations are taken into account, namely shift and scale in a width and height, angle, changes in intensity and contrast. The software for image alignment of objects has been created using Delphi environment. The program utilizes modified genetic algorithms where the chromosomes are the vectors of real numbers. The methods of roulette, rank and tournament selection are used for chromosome selection. After the use of the genetic algorithm the object images were compared by the method of coordinate descent that provides an accuracy improvement of image alignment. The efficiency of different methods of chromosome selection in the genetic algorithm for images alignment is researched. The size of chromosome population as well as other parameters of genetic algorithm have been optimized.

References

V.Y. Kutkovetskyy, Pattern Recognition: Training Manual, Mykolaiv, Publ. MSHU of P. Mohyla, 2003, 196 p. (in Ukrainian)

D. Forsyth, J. Ponce, Computer Vision: A Modern Approach, Moscow, Williams, 2004, 928 p. (in Russian)

R. Gonzalez, R. Woods, Digital Image Processing, Prentice Hall, 2002, 813 p.

S.G. Hoggar, Mathematics of Digital Images. Creation, Compression, Restoration, Recognition, Cambridge University Press, 2006, 853 p.

Image Superposition: http://aicommunity.narod.ru.Reports/Inex/ImageSuperposition.htm. (in Russian)

D. Rutkovskaya, M. Pylynskyy, L. Rutkovskyy, Neural Network, Genetic Algorithms and Fuzzy Logic Systems, Moscow, Hotline – Telecom, 2004, 452 p. (in Russian)

N.B. Paklyn, M.A. Senylov, V.A. Tenenev, Intellectual models based hybrid genetic algorithm with gradient leaders education, Artificial Intelligence, Donetsk: Science and Education, (4) (2004), pp. 159-168. (in Ukrainian)

S.N. Sivanandam, S.N. Deepa, Introduction to Genetic Algorithms, Berlin, Springer-Verlag, 2008, 442 p.

I.Fodchuk, S.Balovsyak, M.Borcha, Ya.Garabazhiv, V.Tkach, Determination of structural inhomogeneity of synthesized diamonds by back scattering electron diffraction, Phys. Status Solidi A, (208) 11 (2011), pp. 2591-2596.

Downloads

Published

2014-08-01

How to Cite

Balovsyak, S., & Fodchuk, I. (2014). OBJECTS IMAGES ALIGNMENT WITH THE USE OF GENETIC AND GRADIENT ALGORITHMS. International Journal of Computing, 12(2), 160-169. https://doi.org/10.47839/ijc.12.2.597

Issue

Section

Articles