A Multi-scale Color Vector Morphological Edge Detection

Mathematical morphology in its original form is a set-theoretical approach to image analysis. It studies image transformations with a simple geometrical interpretation and their algebraic decomposition and synthesis in terms of elementary set operations. Mathematical Morphology has been applied in many fields, at the beginning, it is only applied in binary images called binary-scale morphology, and then it has been developed to gray-level images called gray-scalemorphology, but there are few researches in color image. In this paper we present a new color vector morphological edge detection methods using a multi-scale approach for detection edge under noisy condition. The goal of edge detection is to detect and localize edge points even under noise condition. Not all edges with various fineness regarding spectral contrast and spatial geometry can be detected by a single operator. In fact, some details that seem to be freak and noisy in one scale may become relevant in other scale. Hence, edges of different fineness are detected using operator at different scale, and then they are judiciously combined to produce all the edges of interest in an image. The experiment has proved this proposed method can detect detail edges in color image. Its superiority has been revealed by comparing with the traditional edge detection methods such as LOG. The experimental results have shown this method is robust to noise.