Journal of Mathematical Problems, Equations and Statistics
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P-ISSN: 2709-9393, E-ISSN: 2709-9407

2024, Vol. 5, Issue 1, Part B


Application of intuitionistic robust fuzzy matrix in computer vision


Author(s): K Revathi and Dr. P Sundararajan

Abstract: Many techniques have been employed for the development of an optimum corner detection algorithm. Each effort is guided by the motivation to overcome the limitations in previous methodologies. The conventional techniques incorporate the use of linear time invariant filters. These filters recognize a corner as an abrupt change of grey scale pixel intensities. The techniques are well established and computationally efficient. Harris, SUSAN, Robert, Prewitt, canny, SOBOL, SIFT, FAST, SFAST are based on the concept of spatial differential filters utilizing local gradient. These filters process the data in a relatively short time and are computationally optimized, however, they are susceptible to noise. In this paper a new intuitionistic robust fuzzy matrix, corner-based detection method is proposed, namely Intuitionistic Robust Fuzzy Matrix Corner Detection (IRFMCD) and its performance is studied by using real images with error tolerance.

DOI: https://doi.org/10.22271/math.2024.v5.i1b.132

Pages: 137-142 | Views: 386 | Downloads: 154

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Journal of Mathematical Problems, Equations and Statistics
How to cite this article:
K Revathi and Dr. P Sundararajan. Application of intuitionistic robust fuzzy matrix in computer vision. Journal of Mathematical Problems, Equations and Statistics. 2024; 5(1): 137-142. DOI: 10.22271/math.2024.v5.i1b.132
Journal of Mathematical Problems, Equations and Statistics
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