Most of embedded cameras use a single sensor to capture images through a color filter. They produce special images with only one color component per pixel. Missing data are usually estimated through a demosaicking process, but this takes undesirable computation time and may generate undesirable color artifacts. Many embedded systems under real-time constraints could use this type of camera for purposes like edge detection. In this paper, a new edge detection method is proposed for the computation of partial derivative images. This algorithm is tested on a large set of synthetic images where edge ground truth is unquestionable. The exploitation of the raw data of images allows not only to drastically reduce computational time, but also to get edge detection results even more precise than using certain demosaicking-based methods.