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Author Meskine, F. ♦ Taleb, N. ♦ El-Mezouar, M. Chikr ♦ Kpalma, K. ♦ Almhdie, A.
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Remote Sensing Image ♦ Genetic Algorithm Hausdorff Distance ♦ Rigid Point Set Registration ♦ Data Set ♦ Feature Point ♦ Hausdorff Distance ♦ Genetic Algorithm ♦ Similarity Measure ♦ Inertial Parallel ♦ Local Curvature Corner ♦ Computer Vision ♦ Abstract Image Registration ♦ Rigid Point Registration Method ♦ Satellite Image ♦ Search Space ♦ Point Correspondence ♦ Common Reference Frame ♦ High Computation Speed ♦ Remote Sensing
Abstract 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.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Publisher Date 2013-01-01