Application of intuitionistic robust fuzzy matrix in computer vision

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.