Abstract:
Typically, the edge detection problem in color images has
been addressed using the Euclidean Distance or similar
metrics. Recently, the Vector Angle metric was introduced
to use the hue and saturation components in a color image
in order to capture more accurate edge data. However,
both the Euclidean Distance and Vector Angle metrics
have some limitations. Two methods which combine both
metrics are introduced. They try to leverage the
advantages of each metric to better detect edges in
complex color images. The edge detection operators used
are based on the Vector Gradient and the Difference
Vector operators. Preliminary results are presented and
discussed.