Edge detection is most popular problem in image analysis. To develop an edge detection method that has efficient computation time, sensing to noise as minimum level and extracting meaningful edges from the image, so that many crowded edge detection algorithms have emerged in this area. The different derivative operators and possible different scales are needed in order to properly determine all meaningful edges in a processed image. In this work, we have combined the edge information obatined from each operators at different scales with the comcept of common vector apprach and obtained edge segments that connected, thin and robust to the noise.