Vector co‐occurrence morphological edge detection for colour image

Abstract

Morphological edge detection is a principal component in pattern recognition and machine vision. Traditional edge detection operators only take pixel mutual into consideration. However, the edges are influenced not only by pixel mutual but also by the boundary characteristics. Here, the vector co-occurrence morphological edge detection operator is proposed, which takes the pixel and boundary information both into consideration. The vector co-occurrence algorithm is exploited to resist the influence of the noise points and detect the edges from the colour image rather than the grey image. And, we lead to define a precise definition of the manner of sorting high-dimensional data for the colour image. The experiment results always illustrate the advancement and practicability of our methods against the baseline method. In terms of experiments, the BSDS500 dataset is introduced to compare and analyse with other algorithms. Based on the standard benchmark index evaluation in the BSDS500 dataset, the ODS and AP of various algorithms are compared and analysed.