  Edge detection is a classic problem in the field of image processing, which
lays foundations for other tasks such as image segmentation. Conventionally,
this operation is performed using gradient operators such as the Roberts or
Sobel operator, which can discover local changes in intensity levels. These
operators, however, perform poorly on low contrast images. In this paper, we
propose an edge detector architecture for color images based on fuzzy theory
and the Sobel operator. First, the R, G and B channels are extracted from an
image and enhanced using fuzzy methods, in order to suppress noise and improve
the contrast between the background and the objects. The Sobel operator is then
applied to each of the channels, which are finally combined into an edge map of
the origin image. Experimental results obtained through an FPGA-based
implementation have proved the proposed method effective.
