TY  - JOUR
AU  - Guelzim, Ibrahim 
AU  - Hammouch, Ahmed 
AU  - Aboutajdine, Driss 
PY  - 2011
TI  - Improvement of Image Matching by using the Proximity Criterion: Application to Omnidirectional and Perspective Images
JF  - Journal of Computer Science
VL  - 7
IS  - 8
DO  - 10.3844/jcssp.2011.1230.1236
UR  - https://thescipub.com/abstract/jcssp.2011.1230.1236
AB  - Problem statement: In computer vision, matching is an important phase for several
applications (object reconstruction, robot navigation ...). The similarity measures used provided
results which could be improved. Approach: This research proposed to improve image matching
by using the proximity criterion. The similarity measures used mutual information and correlation
coefficient. The matching was done between neighborhoods of points of interest extracted from the
images. The second chance algorithm was also applied. We have worked in case which the
sensor had a slight displacement between two images. The tests were performed on
omnidirectional and perspective grayscale images. Results: The improvement by introducing
the proximity criterion reached 15.9% for non-noised perspective images, 32.1% for noised
perspective images, 47.69% for non-noised omnidirectional images and 58.5% for noised
omnidirectional images. Conclusion/Recommendations: The introduction of the proximity
criterion has significantly improved the performance of the matching. The method is
recommended in mobile robotics, knowing that a good matching leads to a better location and
better movement of the robot.