Stereo depth estimation using synchronous optimization with segment based regularization

Aydın, Tarkan; Akgül, Yusuf Sinan

doi:10.1016/j.patrec.2010.07.012

Cited by 5 publications

(1 citation statement)

References 35 publications

(30 reference statements)

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“…If the neighborhood size is reduced, the information available for matching is depleted by cons if the neighborhood size is large the information is more reliable statistically, but the probability of occultation is higher (Keck and Davis, 2011). Other authors have proposed to vary the window size depending on the texture (Aydin and Akgul 2010).…”

Section: Introductionmentioning

confidence: 99%

Improvement of Image Matching by using the Proximity Criterion: Application to Omnidirectional and Perspective Images

Guelzim¹,

Hammouch²,

Aboutajdine³

2011

Journal of Computer Science

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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

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Section: Introductionmentioning

confidence: 99%