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General Information
    • ISSN: 2010-3700
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus(since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2019 Vol.9(1): 62-66 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2019.9.1.766

Robust Harris Detector Corresponding and Calculates the Projection Error Using the Modification of the Weighting Function

A. Chater and A. Lasfar
Abstract—Epipolar geometry is a key point in computer vision and the fundamental matrix estimation. The relational view can be obtained from the fundamental matrix. In this way, we interest to calculate an exact matrix based from characteristics unequally distributed in complex scene images. This paper presents a method based on the detection of points by the Harris detector, after we develop a new modification of the multi-level function related to the M-estimator algorithm. The experimental comparisons were conducted by a simulation between RANSAC, LMeds, and M-Estimator in order to estimate the projection error. As a result, the proposed method gives a significant improvement and performance with a low projection error compared to other methods.

Index Terms—Epipolar geometry, fundamental matrix, weighting function, projection error, Harris detector.

The authors are with Laboratory of System Analysis, Information Processing and Industry Management, High School of Technology SALE Mohammed V University, Rabat, Morocco (e-mail: ahmedchater11@gmail.com, ali.lasfar@gmail.com.com).

[PDF]

Cite: A. Chater and A. Lasfar, "Robust Harris Detector Corresponding and Calculates the Projection Error Using the Modification of the Weighting Function," International Journal of Machine Learning and Computing vol. 9, no. 1, pp. 62-66, 2019.

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