To simplify computation and to achieve higher positioning accuracy, a Sum and Difference of Neighborhoods along Axis(SDNAA)algorithm was proposed to implement the edge detection of a microscopic image with a lower signal-to-noise ratio and lower transition. Firstly, characteristics of gray profile of the line microscopic image was analyzed and the inadequacy of derivative based edge detection was analyzed according to the configuration of the microscope imaging system. Then, the computation was defined for the SDNAA algorithm based on the orientation information measure, and the SDNAA edge detection algorithm was derived according to the moment invariant theory. Experimental results indicate that the SDNAA algorithm adapts to different resolution images. It has strong anti-noise ability and high positioning accuracy, which is superior to that of the derivative based edge detection algorithm. Using the algorithm for microscopic images with low signal-to-noise ratio and low contrast, the variance of located edge coordinates is 0.57 pixel, and the measurement result of micro line width deviates from that of SEM (1.35 μm) by 0.17 μm, which reaches the expected precision.