@article{MAKHILLJEAS201813715957,
    title = {Detection of Image Descriptors and Modification of the Weighting Function for the
Estimation of the Fundamental Matrix Using Robust Methods},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {13},
    number = {7},
    pages = {1835-1843},
    year = {2018},
    issn = {1816-949x},
    doi = {jeasci.2018.1835.1843},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2018.1835.1843},
    author = {A. and},
    keywords = {Epipolar geometry,estimate fundamental matrix,robust methods,Gaussian noise,evaluate Sampson error,segmentation,weighting function},
    abstract = {The computer vision is one of the most important specialties which can contribute on development
of the computing. The estimation of the fundamental matrix remains a necessary tool to obtain and evaluate the
relationships between two different view images. Different methods of segmentation exist to satisfy the
specification of elimination of the false correspondence point. In this study, we propose a method based on
the image segmentation using the super pixel algorithm. After that, we develop a new modification on the
weighting function related with the fundamental matrix. Experimental comparisons were conducted through a
simulation between the RANSAC, LMed, M-estimator and our method in order to estimate the projection error.
Consequently, the proposed method gives a good performance results with a low error of projection compared
to the others robust methods.}
    }