A Method of Counting Distances (MCD) was proposed to improve the efficiency of iris recognition in this paper. The MCD was used in a denoising for iris edge image, and efficient location methods for both inner and outer circles of the iris were established. First, a method of grey level summation was utilized to find a pixel in the pupil, meanwhile, the iris edge image could be obtained by using the Canny operator, and three edge points of iris inner edge could be found according to the pixel in the pupil. Then, three edge points were derived to the equation of a circle to find the iris inner edge by substituting. Furthermore, the noises in iris outer edge image were eliminated in terms of the inner location data, and 20 percent of the edge points far from the center of inner circle of the iris were excluded from the denoised edge image. Finally, an improved Hough transformation was used to obtain the data of iris outer edge. Experimental results show that both inner and outer location time obtained using MCD is lower than those obtained by the Fast and Accurate Iris Location Algorithm (FAILA), and the success rate of MCD is 96.67%, which is higher than that of FAILA. Thus, the MCD has high precision and fast speed, and can lay the foundation for improving the efficiency of iris recognition.