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.