@article{(Open Science Index):https://publications.waset.org/pdf/16026,
	  title     = {A Rigid Point Set Registration of Remote Sensing Images Based on Genetic Algorithms and Hausdorff Distance},
	  author    = {F. Meskine and  N. Taleb and  M. Chikr El-Mezouar and  K. Kpalma and  A. Almhdie},
	  country	= {},
	  institution	= {},
	  abstract     = {Image registration is the process of establishing point
by point correspondence between images obtained from a same
scene. This process is very useful in remote sensing, medicine,
cartography, computer vision, etc. Then, the task of registration is to
place the data into a common reference frame by estimating the
transformations between the data sets. In this work, we develop a
rigid point registration method based on the application of genetic
algorithms and Hausdorff distance. First, we extract the feature points
from both images based on the algorithm of global and local
curvature corner. After refining the feature points, we use Hausdorff
distance as similarity measure between the two data sets and for
optimizing the search space we use genetic algorithms to achieve
high computation speed for its inertial parallel. The results show the
efficiency of this method for registration of satellite images.},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {7},
	  number    = {6},
	  year      = {2013},
	  pages     = {752 - 757},
	  ee        = {https://publications.waset.org/pdf/16026},
	  url   	= {https://publications.waset.org/vol/78},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 78, 2013},